This editorial explores the significant challenge of intensive care unit-acquiredweakness(ICU-AW),a prevalent condition affecting critically ill patients,characterizedby profound muscle weakness and complicating patie...This editorial explores the significant challenge of intensive care unit-acquiredweakness(ICU-AW),a prevalent condition affecting critically ill patients,characterizedby profound muscle weakness and complicating patient recovery.Highlightingthe paradox of modern medical advances,it emphasizes the urgent needfor early identification and intervention to mitigate ICU-AW's impact.Innovatively,the study by Wang et al is showcased for employing a multilayer perceptronneural network model,achieving high accuracy in predicting ICU-AWrisk.This advancement underscores the potential of neural network models inenhancing patient care but also calls for continued research to address limitationsand improve model applicability.The editorial advocates for the developmentand validation of sophisticated predictive tools,aiming for personalized carestrategies to reduce ICU-AW incidence and severity,ultimately improving patientoutcomes in critical care settings.展开更多
Early identification and treatment of stroke can greatly improve patient outcomes and quality of life.Although clinical tests such as the Cincinnati Pre-hospital Stroke Scale(CPSS)and the Face Arm Speech Test(FAST)are...Early identification and treatment of stroke can greatly improve patient outcomes and quality of life.Although clinical tests such as the Cincinnati Pre-hospital Stroke Scale(CPSS)and the Face Arm Speech Test(FAST)are commonly used for stroke screening,accurate administration is dependent on specialized training.In this study,we proposed a novel multimodal deep learning approach,based on the FAST,for assessing suspected stroke patients exhibiting symptoms such as limb weakness,facial paresis,and speech disorders in acute settings.We collected a dataset comprising videos and audio recordings of emergency room patients performing designated limb movements,facial expressions,and speech tests based on the FAST.We compared the constructed deep learning model,which was designed to process multi-modal datasets,with six prior models that achieved good action classification performance,including the I3D,SlowFast,X3D,TPN,TimeSformer,and MViT.We found that the findings of our deep learning model had a higher clinical value compared with the other approaches.Moreover,the multi-modal model outperformed its single-module variants,highlighting the benefit of utilizing multiple types of patient data,such as action videos and speech audio.These results indicate that a multi-modal deep learning model combined with the FAST could greatly improve the accuracy and sensitivity of early stroke identification of stroke,thus providing a practical and powerful tool for assessing stroke patients in an emergency clinical setting.展开更多
Esophageal cancer ranks among the most prevalent malignant tumors globally,primarily due to its highly aggressive nature and poor survival rates.According to the 2020 global cancer statistics,there were approximately ...Esophageal cancer ranks among the most prevalent malignant tumors globally,primarily due to its highly aggressive nature and poor survival rates.According to the 2020 global cancer statistics,there were approximately 604000 new cases of esophageal cancer,resulting in 544000 deaths.The 5-year survival rate hovers around a mere 15%-25%.Notably,distinct variations exist in the risk factors associated with the two primary histological types,influencing their worldwide incidence and distribution.Squamous cell carcinoma displays a high incidence in specific regions,such as certain areas in China,where it meets the cost-effect-iveness criteria for widespread endoscopy-based early diagnosis within the local population.Conversely,adenocarcinoma(EAC)represents the most common histological subtype of esophageal cancer in Europe and the United States.The role of early diagnosis in cases of EAC originating from Barrett's esophagus(BE)remains a subject of controversy.The effectiveness of early detection for EAC,particularly those arising from BE,continues to be a debated topic.The variations in how early-stage esophageal carcinoma is treated in different regions are largely due to the differing rates of early-stage cancer diagnoses.In areas with higher incidences,such as China and Japan,early diagnosis is more common,which has led to the advancement of endoscopic methods as definitive treatments.These techniques have demonstrated remarkable efficacy with minimal complications while preserving esophageal functionality.Early screening,prompt diagnosis,and timely treatment are key strategies that can significantly lower both the occurrence and death rates associated with esophageal cancer.展开更多
BACKGROUND Multiple endocrine neoplasias(MENs)are a group of hereditary diseases invol-ving multiple endocrine glands,and their prevalence is low.MEN type 1(MEN1)has diverse clinical manifestations,mainly involving th...BACKGROUND Multiple endocrine neoplasias(MENs)are a group of hereditary diseases invol-ving multiple endocrine glands,and their prevalence is low.MEN type 1(MEN1)has diverse clinical manifestations,mainly involving the parathyroid glands,gastrointestinal tract,pancreas and pituitary gland,making it easy to miss the clinical diagnosis.CASE SUMMARY We present the case of a patient in whom MEN1 was detected early.A middle-aged male with recurrent abdominal pain and diarrhea was admitted to the hos-pital.Blood tests at admission revealed hypercalcemia and hypophosphatemia,and emission computed tomography of the parathyroid glands revealed a hy-perfunctioning parathyroid lesion.Gastroscopy findings suggested a duodenal bulge and ulceration.Ultrasound endoscopy revealed a hypoechoic lesion in the duodenal bulb.Further blood tests revealed elevated levels of serum gastrin.Surgery was performed,and pathological analysis of the surgical specimens revealed a parathyroid adenoma after parathyroidectomy and a neuroendocrine tumor after duodenal bulbectomy.The time from onset to the definitive diagnosis of MEN1 was only approximately 1 year.CONCLUSION For patients who present with gastrointestinal symptoms accompanied by hyper-calcemia and hypophosphatemia,clinicians need to be alert to the possibility of MEN1.展开更多
This editorial comments on the article by Qu et al in a recent edition of World Journal of Gastrointestinal Oncology,focusing on the importance of early diagnosis in managing esophageal cancer and strategies for achie...This editorial comments on the article by Qu et al in a recent edition of World Journal of Gastrointestinal Oncology,focusing on the importance of early diagnosis in managing esophageal cancer and strategies for achieving“early detection”.The five-year age-standardized net survival for esophageal cancer patients falls short of expectations.Early detection and accurate diagnosis are critical strategies for improving the treatment outcomes of esophageal cancer.While advancements in endoscopic technology have been significant,there seems to be an excessive emphasis on the latest high-end endoscopic devices and various endoscopic resection techniques.Therefore,it is imperative to redirect focus towards proactive early detection strategies for esophageal cancer,investigate the most cost-effective screening methods suitable for different regions,and persistently explore practical solutions to improve the five-year survival rate of patients with esophageal cancer.展开更多
In recent years,early detection and warning of fires have posed a significant challenge to environmental protection and human safety.Deep learning models such as Faster R-CNN(Faster Region based Convolutional Neural N...In recent years,early detection and warning of fires have posed a significant challenge to environmental protection and human safety.Deep learning models such as Faster R-CNN(Faster Region based Convolutional Neural Network),YOLO(You Only Look Once),and their variants have demonstrated superiority in quickly detecting objects from images and videos,creating new opportunities to enhance automatic and efficient fire detection.The YOLO model,especially newer versions like YOLOv10,stands out for its fast processing capability,making it suitable for low-latency applications.However,when applied to real-world datasets,the accuracy of fire prediction is still not high.This study improves the accuracy of YOLOv10 for real-time applications through model fine-tuning techniques and data augmentation.The core work of the research involves creating a diverse fire image dataset specifically suited for fire detection applications in buildings and factories,freezing the initial layers of the model to retain general features learned from the dataset by applying the Squeeze and Excitation attention mechanism and employing the Stochastic Gradient Descent(SGD)with a momentum optimization algorithm to enhance accuracy while ensuring real-time fire detection.Experimental results demonstrate the effectiveness of the proposed fire prediction approach,where the YOLOv10 small model exhibits the best balance compared to other YOLO family models such as nano,medium,and balanced.Additionally,the study provides an experimental evaluation to highlight the effectiveness of model fine-tuning compared to the YOLOv10 baseline,YOLOv8 and Faster R-CNN based on two criteria:accuracy and prediction time.展开更多
The screening of colorectal cancer(CRC)is pivotal for both the prevention and treatment of this disease,significantly improving early-stage tumor detection rates.This advancement not only boosts survival rates and qua...The screening of colorectal cancer(CRC)is pivotal for both the prevention and treatment of this disease,significantly improving early-stage tumor detection rates.This advancement not only boosts survival rates and quality of life for patients but also reduces the costs associated with treatment.However,the adoption of CRC screening methods faces numerous challenges,including the technical limitations of both noninvasive and invasive methods in terms of sensitivity and specificity.Moreover,socioeconomic factors such as regional disparities,economic conditions,and varying levels of awareness affect screening uptake.The coronavirus disease 2019 pandemic further intensified these challenges,leading to reduced screening participation and increased waiting periods.Additionally,the growing prevalence of early-onset CRC necessitates innovative screening approaches.In response,research into new methodologies,including artificial intelligence-based systems,aims to improve the precision and accessibility of screening.Proactive measures by governments and health organizations to enhance CRC screening efforts are underway,including increased advocacy,improved service delivery,and international cooperation.The role of technological innovation and global health collaboration in advancing CRC screening is undeniable.Technologies such as artificial intelligence and gene sequencing are set to revolutionize CRC screening,making a significant impact on the fight against this disease.Given the rise in early-onset CRC,it is crucial for screening strategies to continually evolve,ensuring their effectiveness and applicability.展开更多
Background: Acute Kidney Injury (AKI) stands as a prominent postoperative complication in on-pump cardiac surgery, with repercussions on morbidity, mortality, and hospitalization duration. Current diagnostic criteria ...Background: Acute Kidney Injury (AKI) stands as a prominent postoperative complication in on-pump cardiac surgery, with repercussions on morbidity, mortality, and hospitalization duration. Current diagnostic criteria relying on serum creatinine levels exhibit a delayed identification of AKI, prompting an exploration of alternative biomarkers. Aims and Objectives: This study is designed to overcome diagnostic constraints and explore the viability of serum Cystatin C as an early predictor of Acute Kidney Injury (AKI) in individuals undergoing on-pump cardiac surgery. The investigation aims to establish the relationship between serum Cystatin C levels and the onset of AKI in patients subjected to on-pump cardiac surgery. Primary objectives involve the assessment of the diagnostic effectiveness of serum Cystatin C, its comparison with serum creatinine, and the exploration of its potential for the early identification and treatment of AKI. Methodology: Conducted as a single-center study at the cardiac surgery department of BSMMU in Bangladesh from September 2020 to August 2022, a comparative cross-sectional analysis involved 31 participants categorized into No AKI and AKI groups based on Kidney Disease: Improving Global Outcomes (KDIGO) criteria. Data collection encompassed preoperative, post-CBP (cardiopulmonary bypass) conclusion at 2 hours, postoperative day 1, and postoperative day 2 intervals. Statistical analyses included Chi-squared tests, independent Student’s t-tests, and one-sample t-tests. Significance was set at P Results: The study revealed no significant differences in baseline characteristics between the No AKI and AKI groups, except for CPB time and cross-clamp time. Serum Cystatin C levels in the AKI group exhibited statistical significance at various time points, highlighting its potential as an early detector. Conversely, Serum Creatinine levels in the AKI group showed no statistical significance. The Receiver Operating Characteristic (ROC) curve analysis further supported the efficacy of serum Cystatin C, with an Area under the ROC Curve of 0.864 and a cut-off value of 0.55 (p Conclusion: This study supports the superior utility of serum Cystatin C as an early detector of AKI in on-pump cardiac surgery patients compared to serum creatinine. Its ability to identify AKI several hours earlier may contribute to reduced morbidity, mortality, and healthcare costs. The findings underscore the significance of exploring novel biomarkers for improved post-cardiac surgery renal function assessment.展开更多
This editorial discusses the literature review article by Tonini and Zanni,the paper was published in January 2024,and the authors provided very interesting conclusions regarding existing barriers to the early diagnos...This editorial discusses the literature review article by Tonini and Zanni,the paper was published in January 2024,and the authors provided very interesting conclusions regarding existing barriers to the early diagnosis of colon cancer.Many cancers do not have identifiable precursors,or there are currently no screening tests to find them.Therefore,these cancers do not have preventive screening options.Early detection is crucial for reducing mortality rates by identifying cancer at an earlier stage through screening,as opposed to no screening.Colorectal cancer develops from precancerous lesions,which can be detected early and potentially prevented and cured.Early detection leads to improved survival rates,decreased complications,and reduced healthcare expenses.This editorial provides a brief description of the biology of colon cancer,emphasizing the contrast in outcomes between early detection and late detection.We also describe screening programs around the globe and examine the barriers in each program.Finally,we explore potential future solutions to enhance inclusion in screening programs and improve patient compliance.展开更多
The coronavirus disease 2019(COVID-19)has currently caused the mortality of millions of people around the world.Aside from the direct mortality from the COVID-19,the indirect effects of the pandemic have also led to a...The coronavirus disease 2019(COVID-19)has currently caused the mortality of millions of people around the world.Aside from the direct mortality from the COVID-19,the indirect effects of the pandemic have also led to an increase in the mortality rate of other non-COVID patients.Evidence indicates that novel COVID-19 pandemic has caused an inflation in acute cardiovascular mortality,which did not relate to COVID-19 infection.It has in fact increased the risk of death in cardiovascular disease(CVD)patients.For this purpose,it is dramatically inevitable to monitor CVD patients’vital signs and to detect abnormal events before the occurrence of any critical conditions resulted in death.Internet of things(IoT)and health monitoring sensors have improved the medical care systems by enabling latency-sensitive surveillance and computing of large amounts of patients’data.The major challenge being faced currently in this problem is its limited scalability and late detection of cardiovascular events in IoT-based computing environments.To this end,this paper proposes a novel framework to early detection of cardiovascular events based on a deep learning architecture in IoT environments.Experimental results showed that the proposed method was able to detect cardiovascular events with better performance(95.30%average sensitivity and 95.94%mean prediction values).展开更多
Time-series data provide important information in many fields,and their processing and analysis have been the focus of much research.However,detecting anomalies is very difficult due to data imbalance,temporal depende...Time-series data provide important information in many fields,and their processing and analysis have been the focus of much research.However,detecting anomalies is very difficult due to data imbalance,temporal dependence,and noise.Therefore,methodologies for data augmentation and conversion of time series data into images for analysis have been studied.This paper proposes a fault detection model that uses time series data augmentation and transformation to address the problems of data imbalance,temporal dependence,and robustness to noise.The method of data augmentation is set as the addition of noise.It involves adding Gaussian noise,with the noise level set to 0.002,to maximize the generalization performance of the model.In addition,we use the Markov Transition Field(MTF)method to effectively visualize the dynamic transitions of the data while converting the time series data into images.It enables the identification of patterns in time series data and assists in capturing the sequential dependencies of the data.For anomaly detection,the PatchCore model is applied to show excellent performance,and the detected anomaly areas are represented as heat maps.It allows for the detection of anomalies,and by applying an anomaly map to the original image,it is possible to capture the areas where anomalies occur.The performance evaluation shows that both F1-score and Accuracy are high when time series data is converted to images.Additionally,when processed as images rather than as time series data,there was a significant reduction in both the size of the data and the training time.The proposed method can provide an important springboard for research in the field of anomaly detection using time series data.Besides,it helps solve problems such as analyzing complex patterns in data lightweight.展开更多
Epidemiological studies showed the incidence mortality rates of cancer were increasing in recent decades in Chinese population.National and regional preventive programs aim to reduce the health hazards of cancer and f...Epidemiological studies showed the incidence mortality rates of cancer were increasing in recent decades in Chinese population.National and regional preventive programs aim to reduce the health hazards of cancer and focuse the population at high risks for specific cancer, particularly in rural areas and to offer the access to early detection for multlple cancers in urban areas. The early screening, early detection and treatment have been put into operation for the population at risks in rural areas at first, and in the urban areas in recent years. To understand the epidemic patterns and trends of cancer, and the experiences in applying early detection strategies in China, selected literatures were reviewed for brief summary.展开更多
AIM To investigate the value of multiparameter joint analysis in the early diagnosis of gastric cancer(GC) in clinical practice.METHODS Concentrations of CEA, CA724 and three kinds of cytokines(TNF-α, IL-6 and IL-8) ...AIM To investigate the value of multiparameter joint analysis in the early diagnosis of gastric cancer(GC) in clinical practice.METHODS Concentrations of CEA, CA724 and three kinds of cytokines(TNF-α, IL-6 and IL-8) in 176 GC patients, 117 atypical hyperplasia patients, and 204 healthy control individuals were used for building the diagnostic model, then 58 GC patients, 41 atypical hyperplasia patients, and 66 healthy control individuals were enrolled independently. The joints of the indicators were analyzed by binary logistic regression analysis method.RESULTS For discriminating the healthy control group and the GC group, IL-6 had the best diagnostic value, and the area under curve(AUC) of joint analysis was 0.95(0.93-0.97). For the early stage and advanced stage GC, the AUC were 0.95(0.92-0.98) and 0.95(0.92-0.97). For discriminating the atypical hyperplasia group and GC group, CA724 had the best diagnostic value, and the AUC of joint analysis was 0.97(0.95-0.99). For the early stage and advanced stage GC groups, the AUC were 0.98(0.96-0.99) and 0.96(0.94-0.98). After evaluation, for discriminating the GC, early stage GC and advanced cancer group from the healthy control group, the diagnostic sensitivity was 89.66%, 84.21% and 92.31%, respectively, and the specificity was 92.42%, 90.91% and 90.91%. For discriminating the GC, early stage GC and advanced cancer groups from the atypical hyperplasia group, the diagnostic sensitivity was 87.93%, 78.95% and 92.31%, respectively, and the specificity was 87.80%, 85.37% and 90.24%.CONCLUSION We have built a diagnostic model including CEA, CA724, IL-6, IL-8, and TNF-α. It may provide potential assistance as a screening method for the early detection of GC.展开更多
This review article summarizes the research advances of the plasma-based SEPT9 gene methylation assay for the clinical detection of colorectal cancer and its limitations. Colorectal cancer is a common malignancy with ...This review article summarizes the research advances of the plasma-based SEPT9 gene methylation assay for the clinical detection of colorectal cancer and its limitations. Colorectal cancer is a common malignancy with a poor prognosis and a high mortality, for which early detection and diagnosis are particularly crucial for the high-risk groups. Increasing evidence supported that SEPT9 gene methylation is associated with the pathogenesis of colorectal cancer and that detecting the level of methylation of SEPT9 in the peripheral blood can be used for screening of colorectal cancer in susceptible populations. In recent years, the data obtained in clinical studies demonstrated that the SEPT9 gene methylation assay has a good diagnostic performance with regard to both sensitivity and specificity with the advantage of better acceptability, convenience and compliance with serological testing compared with fecal occult blood tests and carcinoembryonic antigen for colorectal cancer(CRC). Furthermore, the combination of multiple methods or markers has become a growing trend for CRC detection and screening. Nevertheless, the clinical availability of the methylated SEPT9 assay is still limited because of the large degree of sample heterogeneity caused by demographic characteristics, pathological features, comorbidities and/or technique selection. Another factor is the cost-effectiveness of colorectal cancer screening strategies that hinders its large-scale application. In addition, improvements in its accuracy in detecting adenomas and premalignant polyps are required.展开更多
Pancreatic ductal adenocarcinoma(PDAC) is one of the most lethal forms of cancer. Substantial progress has been made in the understanding of the biology of pancreatic cancer, and advances in patient management have be...Pancreatic ductal adenocarcinoma(PDAC) is one of the most lethal forms of cancer. Substantial progress has been made in the understanding of the biology of pancreatic cancer, and advances in patient management have been significant. However, most patients(nearly80%) who present with locally advanced or metastatic disease have an extremely poor prognosis. Survival is better for those with malignant disease localized to the pancreas, because surgical resection at present offers the only chance of cure. Therefore, the early detection of pancreatic cancer may benefit patients with PDAC.However, its low rate of incidence and the limitations of current screening strategies make early detection difficult. Recent advances in the understanding of the pathogenesis of PDAC suggest that it is possible to detect PDAC in early stages and even identify precursor lesions. The presence of new-onset diabetes mellitus in the early phase of pancreatic cancer may provide cluesfor its early diagnosis. Advances in the identification of novel circulating biomarkers including serological signatures, autoantibodies, epigenetic markers, circulating tumor cells and microRNAs suggest that they can be used as potential tools for the screening of precursors and early stage PDAC in the future. However, proper screening strategies based on effective screening methodologies need to be tested for clinical application.展开更多
AIM In our previous study, we have built a nine-gene(GPC3, HGF, ANXA1, FOS, SPAG9, HSPA1 B, CXCR4, PFN1, and CALR) expression detection system based on the Ge XP system. Based on peripheral blood and Ge XP, we aimed t...AIM In our previous study, we have built a nine-gene(GPC3, HGF, ANXA1, FOS, SPAG9, HSPA1 B, CXCR4, PFN1, and CALR) expression detection system based on the Ge XP system. Based on peripheral blood and Ge XP, we aimed to analyze the results of genes expression by different multi-parameter analysis methods and build a diagnostic model to classify hepatocellular carcinoma(HCC) patients and healthy people.METHODS Logistic regression analysis, discriminant analysis, classification tree analysis, and artificial neural network were used for the multi-parameter gene expression analysis method. One hundred and three patients with early HCC and 54 age-matched healthy normal controls were used to build a diagnostic model. Fiftytwo patients with early HCC and 34 healthy people were used for validation. The area under the curve, sensitivity, and specificity were used as diagnostic indicators.RESULTS Artificial neural network of the total nine genes had the best diagnostic value, and the AUC, sensitivity, and specificity were 0.943, 98%, and 85%, respectively. At last, 52 HCC patients and 34 healthy normal controls were used for validation. The sensitivity and specificity were 96% and 86%, respectively.CONCLUSION Multi-parameter analysis methods may increase the diagnostic value compared to single factor analysis and they may be a trend of the clinical diagnosis in the future.展开更多
Lung cancer is associated with a heavy cancer-related burden in terms of patients’physical and mental health worldwide.Two randomized controlled trials,the US-National Lung Screening Trial(NLST)and Nederlands-Leuvens...Lung cancer is associated with a heavy cancer-related burden in terms of patients’physical and mental health worldwide.Two randomized controlled trials,the US-National Lung Screening Trial(NLST)and Nederlands-Leuvens Longkanker Screenings Onderzoek(NELSON),indicated that low-dose CT(LDCT)screening results in a statistically significant decrease in mortality in patients with lung cancer,LDCT has become the standard approach for lung cancer screening.However,many issues in lung cancer screening remain unresolved,such as the screening criteria,high false-positive rate,and radiation exposure.This review first summarizes recent studies on lung cancer screening from the US,Europe,and Asia,and discusses risk-based selection for screening and the related issues.Second,an overview of novel techniques for the differential diagnosis of pulmonary nodules,including artificial intelligence and molecular biomarker-based screening,is presented.Third,current explorations of strategies for suspected malignancy are summarized.Overall,this review aims to help clinicians understand recent progress in lung cancer screening and alleviate the burden of lung cancer.展开更多
AIM:To evaluate the difference in diagnostic performance of hydro-stomach computed tomography(CT) to detect early gastric cancer(EGC) between blinded and unblinded analysis and to assess independent factors affecting ...AIM:To evaluate the difference in diagnostic performance of hydro-stomach computed tomography(CT) to detect early gastric cancer(EGC) between blinded and unblinded analysis and to assess independent factors affecting visibility of cancer foci.METHODS:Two radiologists initially blinded and then unblinded to gastroscopic and surgical-histological findings independently reviewed hydro-stomach CT images of 110 patients with single EGC.They graded the visibility of cancer foci for each of three gastric segments(upper,middle and lower thirds) using a 4-point scale(1:definitely absent,2:probably absent,3:probably present,and 4:definitely present).The sensitivity and specificity for detecting an EGC were calculated.Intraobserver and interobserver agreements were analyzed.The visibility of an EGC was evaluated with regard to tumor size,invasion depth,gastric segments,histological type and gross morphology using univariate and multivariate analysis.RESULTS:The respective sensitivities and specificities [reviewer 1:blinded,20%(22/110) and 98%(215/220);unblinded,27%(30/110) and 100%(219/220)/reviewer 2:blinded,19%(21/110) and 98%(216/220);unblinded,25%(27/110) and 98%(215/220)] were not significantly different.Although intraobserver agreements were good(weighted κ = 0.677 and 0.666),interobserver agreements were fair(blinded,0.371) or moderate(unblinded,0.558).For both univariate and multivariate analyses,the tumor size and invasion depth were statistically significant factors affecting visibility.CONCLUSION:The diagnostic performance of hydrostomach CT to detect an EGC was not significantly different between blinded and unblinded analysis.The tumor size and invasion depth were independent factors for visibility.展开更多
Wi-Fi devices have limited battery life because of which conserving battery life is imperative. The 802.11 Wi-Fi standard provides power management feature that allows stations(STAs) to enter into sleep state to prese...Wi-Fi devices have limited battery life because of which conserving battery life is imperative. The 802.11 Wi-Fi standard provides power management feature that allows stations(STAs) to enter into sleep state to preserve energy without any frame losses. After the STA wakes up, it sends a null data or PS-Poll frame to retrieve frame(s) buffered by the access point(AP), if any during its sleep period. An attacker can launch a power save denial of service(PS-DoS) attack on the sleeping STA(s) by transmitting a spoofed null data or PS-Poll frame(s) to retrieve the buffered frame(s) of the sleeping STA(s) from the AP causing frame losses for the targeted STA(s). Current approaches to prevent or detect the PS-DoS attack require encryption,change in protocol or installation of proprietary hardware. These solutions suffer from expensive setup, maintenance, scalability and deployment issues. The PS-DoS attack does not differ in semantics or statistics under normal and attack circumstances.So signature and anomaly based intrusion detection system(IDS) are unfit to detect the PS-DoS attack. In this paper we propose a timed IDS based on real time discrete event system(RTDES) for detecting PS-DoS attack. The proposed DES based IDS overcomes the drawbacks of existing systems and detects the PS-DoS attack with high accuracy and detection rate. The correctness of the RTDES based IDS is proved by experimenting all possible attack scenarios.展开更多
To review the present status of breast cancer(BC) screening/early detection in low- and middle-income countries(LMICs) and identify the way forward, an open focused search for articles was undertaken in Pub Med, Googl...To review the present status of breast cancer(BC) screening/early detection in low- and middle-income countries(LMICs) and identify the way forward, an open focused search for articles was undertaken in Pub Med, Google Scholar and Google, and using a snowball technique, further articles were obtained from the reference list of initial search results. In addition, a query was put up on Research Gate to obtain more references and find out the general opinion of experts on the topic. Experts were also personally contacted for their opinion. Breast cancer(BC) is the most common cancer in women in the world. The rise in incidence is highest in LMICs where the incidence has often been much lower than high-income countries. In spite of more women dying of cancer than pregnancy or childbirth related causes in LMICs, most of the focus and resources are devoted to maternal health. Also, the majority of women in LMICs present at late stages to a hospital to initiate treatment. A number of trials have been conducted in various LMICs regarding the use of clinical breast examination and mammography in various combinations to understand the best ways of implementing a population level screening/early detection of BC; nevertheless, more research in this area is badly needed for different LMIC specific contexts. No-tably, very few LMICs have national level programs for BC prevention via screening/early detection and even stage reduction is not on the public health agenda. This is in addition to other barriers such as lack of awareness among women regarding BC and the presence of stigma, inappropriate attitudes and lack of following proper screening behavior, such as conducting breast self-examinations. The above is mixed with the apathy and lack of awareness of policy makers regarding the fact that BC prevention is much more cost-effective and humane than BC treatment. Implementation of population level programs for screening/early detection of BC, along with use of ways to improve awareness of women regarding BC, can prove critical in stemming the increasing burden of BC in LMICs. Use of newer modalities such as ultrasonography which is more suited to LMIC populations and use of m Health for awareness creation and increasing screening compliance are much needed extra additions to the overall agenda of LMICs in preventing BC.展开更多
文摘This editorial explores the significant challenge of intensive care unit-acquiredweakness(ICU-AW),a prevalent condition affecting critically ill patients,characterizedby profound muscle weakness and complicating patient recovery.Highlightingthe paradox of modern medical advances,it emphasizes the urgent needfor early identification and intervention to mitigate ICU-AW's impact.Innovatively,the study by Wang et al is showcased for employing a multilayer perceptronneural network model,achieving high accuracy in predicting ICU-AWrisk.This advancement underscores the potential of neural network models inenhancing patient care but also calls for continued research to address limitationsand improve model applicability.The editorial advocates for the developmentand validation of sophisticated predictive tools,aiming for personalized carestrategies to reduce ICU-AW incidence and severity,ultimately improving patientoutcomes in critical care settings.
基金supported by the Ministry of Science and Technology of China,No.2020AAA0109605(to XL)Meizhou Major Scientific and Technological Innovation PlatformsProjects of Guangdong Provincial Science & Technology Plan Projects,No.2019A0102005(to HW).
文摘Early identification and treatment of stroke can greatly improve patient outcomes and quality of life.Although clinical tests such as the Cincinnati Pre-hospital Stroke Scale(CPSS)and the Face Arm Speech Test(FAST)are commonly used for stroke screening,accurate administration is dependent on specialized training.In this study,we proposed a novel multimodal deep learning approach,based on the FAST,for assessing suspected stroke patients exhibiting symptoms such as limb weakness,facial paresis,and speech disorders in acute settings.We collected a dataset comprising videos and audio recordings of emergency room patients performing designated limb movements,facial expressions,and speech tests based on the FAST.We compared the constructed deep learning model,which was designed to process multi-modal datasets,with six prior models that achieved good action classification performance,including the I3D,SlowFast,X3D,TPN,TimeSformer,and MViT.We found that the findings of our deep learning model had a higher clinical value compared with the other approaches.Moreover,the multi-modal model outperformed its single-module variants,highlighting the benefit of utilizing multiple types of patient data,such as action videos and speech audio.These results indicate that a multi-modal deep learning model combined with the FAST could greatly improve the accuracy and sensitivity of early stroke identification of stroke,thus providing a practical and powerful tool for assessing stroke patients in an emergency clinical setting.
基金Supported by Shandong Province Medical and Health Science and Technology Development Plan Project,No.202203030713Clinical Research Funding of Shandong Medical Association-Qilu Specialization,No.YXH2022ZX02031Science and Technology Program of Yantai Affiliated Hospital of Binzhou Medical University,No.YTFY2022KYQD06.
文摘Esophageal cancer ranks among the most prevalent malignant tumors globally,primarily due to its highly aggressive nature and poor survival rates.According to the 2020 global cancer statistics,there were approximately 604000 new cases of esophageal cancer,resulting in 544000 deaths.The 5-year survival rate hovers around a mere 15%-25%.Notably,distinct variations exist in the risk factors associated with the two primary histological types,influencing their worldwide incidence and distribution.Squamous cell carcinoma displays a high incidence in specific regions,such as certain areas in China,where it meets the cost-effect-iveness criteria for widespread endoscopy-based early diagnosis within the local population.Conversely,adenocarcinoma(EAC)represents the most common histological subtype of esophageal cancer in Europe and the United States.The role of early diagnosis in cases of EAC originating from Barrett's esophagus(BE)remains a subject of controversy.The effectiveness of early detection for EAC,particularly those arising from BE,continues to be a debated topic.The variations in how early-stage esophageal carcinoma is treated in different regions are largely due to the differing rates of early-stage cancer diagnoses.In areas with higher incidences,such as China and Japan,early diagnosis is more common,which has led to the advancement of endoscopic methods as definitive treatments.These techniques have demonstrated remarkable efficacy with minimal complications while preserving esophageal functionality.Early screening,prompt diagnosis,and timely treatment are key strategies that can significantly lower both the occurrence and death rates associated with esophageal cancer.
基金Supported by Sanming Project of Medicine in Shenzhen,No.SZSM202211029。
文摘BACKGROUND Multiple endocrine neoplasias(MENs)are a group of hereditary diseases invol-ving multiple endocrine glands,and their prevalence is low.MEN type 1(MEN1)has diverse clinical manifestations,mainly involving the parathyroid glands,gastrointestinal tract,pancreas and pituitary gland,making it easy to miss the clinical diagnosis.CASE SUMMARY We present the case of a patient in whom MEN1 was detected early.A middle-aged male with recurrent abdominal pain and diarrhea was admitted to the hos-pital.Blood tests at admission revealed hypercalcemia and hypophosphatemia,and emission computed tomography of the parathyroid glands revealed a hy-perfunctioning parathyroid lesion.Gastroscopy findings suggested a duodenal bulge and ulceration.Ultrasound endoscopy revealed a hypoechoic lesion in the duodenal bulb.Further blood tests revealed elevated levels of serum gastrin.Surgery was performed,and pathological analysis of the surgical specimens revealed a parathyroid adenoma after parathyroidectomy and a neuroendocrine tumor after duodenal bulbectomy.The time from onset to the definitive diagnosis of MEN1 was only approximately 1 year.CONCLUSION For patients who present with gastrointestinal symptoms accompanied by hyper-calcemia and hypophosphatemia,clinicians need to be alert to the possibility of MEN1.
基金Supported by the Education and Teaching Reform Project,the First Clinical College of Chongqing Medical University,No.CMER202305Program for Youth Innovation in Future Medicine,Chongqing Medical University,No.W0138.
文摘This editorial comments on the article by Qu et al in a recent edition of World Journal of Gastrointestinal Oncology,focusing on the importance of early diagnosis in managing esophageal cancer and strategies for achieving“early detection”.The five-year age-standardized net survival for esophageal cancer patients falls short of expectations.Early detection and accurate diagnosis are critical strategies for improving the treatment outcomes of esophageal cancer.While advancements in endoscopic technology have been significant,there seems to be an excessive emphasis on the latest high-end endoscopic devices and various endoscopic resection techniques.Therefore,it is imperative to redirect focus towards proactive early detection strategies for esophageal cancer,investigate the most cost-effective screening methods suitable for different regions,and persistently explore practical solutions to improve the five-year survival rate of patients with esophageal cancer.
文摘In recent years,early detection and warning of fires have posed a significant challenge to environmental protection and human safety.Deep learning models such as Faster R-CNN(Faster Region based Convolutional Neural Network),YOLO(You Only Look Once),and their variants have demonstrated superiority in quickly detecting objects from images and videos,creating new opportunities to enhance automatic and efficient fire detection.The YOLO model,especially newer versions like YOLOv10,stands out for its fast processing capability,making it suitable for low-latency applications.However,when applied to real-world datasets,the accuracy of fire prediction is still not high.This study improves the accuracy of YOLOv10 for real-time applications through model fine-tuning techniques and data augmentation.The core work of the research involves creating a diverse fire image dataset specifically suited for fire detection applications in buildings and factories,freezing the initial layers of the model to retain general features learned from the dataset by applying the Squeeze and Excitation attention mechanism and employing the Stochastic Gradient Descent(SGD)with a momentum optimization algorithm to enhance accuracy while ensuring real-time fire detection.Experimental results demonstrate the effectiveness of the proposed fire prediction approach,where the YOLOv10 small model exhibits the best balance compared to other YOLO family models such as nano,medium,and balanced.Additionally,the study provides an experimental evaluation to highlight the effectiveness of model fine-tuning compared to the YOLOv10 baseline,YOLOv8 and Faster R-CNN based on two criteria:accuracy and prediction time.
文摘The screening of colorectal cancer(CRC)is pivotal for both the prevention and treatment of this disease,significantly improving early-stage tumor detection rates.This advancement not only boosts survival rates and quality of life for patients but also reduces the costs associated with treatment.However,the adoption of CRC screening methods faces numerous challenges,including the technical limitations of both noninvasive and invasive methods in terms of sensitivity and specificity.Moreover,socioeconomic factors such as regional disparities,economic conditions,and varying levels of awareness affect screening uptake.The coronavirus disease 2019 pandemic further intensified these challenges,leading to reduced screening participation and increased waiting periods.Additionally,the growing prevalence of early-onset CRC necessitates innovative screening approaches.In response,research into new methodologies,including artificial intelligence-based systems,aims to improve the precision and accessibility of screening.Proactive measures by governments and health organizations to enhance CRC screening efforts are underway,including increased advocacy,improved service delivery,and international cooperation.The role of technological innovation and global health collaboration in advancing CRC screening is undeniable.Technologies such as artificial intelligence and gene sequencing are set to revolutionize CRC screening,making a significant impact on the fight against this disease.Given the rise in early-onset CRC,it is crucial for screening strategies to continually evolve,ensuring their effectiveness and applicability.
文摘Background: Acute Kidney Injury (AKI) stands as a prominent postoperative complication in on-pump cardiac surgery, with repercussions on morbidity, mortality, and hospitalization duration. Current diagnostic criteria relying on serum creatinine levels exhibit a delayed identification of AKI, prompting an exploration of alternative biomarkers. Aims and Objectives: This study is designed to overcome diagnostic constraints and explore the viability of serum Cystatin C as an early predictor of Acute Kidney Injury (AKI) in individuals undergoing on-pump cardiac surgery. The investigation aims to establish the relationship between serum Cystatin C levels and the onset of AKI in patients subjected to on-pump cardiac surgery. Primary objectives involve the assessment of the diagnostic effectiveness of serum Cystatin C, its comparison with serum creatinine, and the exploration of its potential for the early identification and treatment of AKI. Methodology: Conducted as a single-center study at the cardiac surgery department of BSMMU in Bangladesh from September 2020 to August 2022, a comparative cross-sectional analysis involved 31 participants categorized into No AKI and AKI groups based on Kidney Disease: Improving Global Outcomes (KDIGO) criteria. Data collection encompassed preoperative, post-CBP (cardiopulmonary bypass) conclusion at 2 hours, postoperative day 1, and postoperative day 2 intervals. Statistical analyses included Chi-squared tests, independent Student’s t-tests, and one-sample t-tests. Significance was set at P Results: The study revealed no significant differences in baseline characteristics between the No AKI and AKI groups, except for CPB time and cross-clamp time. Serum Cystatin C levels in the AKI group exhibited statistical significance at various time points, highlighting its potential as an early detector. Conversely, Serum Creatinine levels in the AKI group showed no statistical significance. The Receiver Operating Characteristic (ROC) curve analysis further supported the efficacy of serum Cystatin C, with an Area under the ROC Curve of 0.864 and a cut-off value of 0.55 (p Conclusion: This study supports the superior utility of serum Cystatin C as an early detector of AKI in on-pump cardiac surgery patients compared to serum creatinine. Its ability to identify AKI several hours earlier may contribute to reduced morbidity, mortality, and healthcare costs. The findings underscore the significance of exploring novel biomarkers for improved post-cardiac surgery renal function assessment.
文摘This editorial discusses the literature review article by Tonini and Zanni,the paper was published in January 2024,and the authors provided very interesting conclusions regarding existing barriers to the early diagnosis of colon cancer.Many cancers do not have identifiable precursors,or there are currently no screening tests to find them.Therefore,these cancers do not have preventive screening options.Early detection is crucial for reducing mortality rates by identifying cancer at an earlier stage through screening,as opposed to no screening.Colorectal cancer develops from precancerous lesions,which can be detected early and potentially prevented and cured.Early detection leads to improved survival rates,decreased complications,and reduced healthcare expenses.This editorial provides a brief description of the biology of colon cancer,emphasizing the contrast in outcomes between early detection and late detection.We also describe screening programs around the globe and examine the barriers in each program.Finally,we explore potential future solutions to enhance inclusion in screening programs and improve patient compliance.
文摘The coronavirus disease 2019(COVID-19)has currently caused the mortality of millions of people around the world.Aside from the direct mortality from the COVID-19,the indirect effects of the pandemic have also led to an increase in the mortality rate of other non-COVID patients.Evidence indicates that novel COVID-19 pandemic has caused an inflation in acute cardiovascular mortality,which did not relate to COVID-19 infection.It has in fact increased the risk of death in cardiovascular disease(CVD)patients.For this purpose,it is dramatically inevitable to monitor CVD patients’vital signs and to detect abnormal events before the occurrence of any critical conditions resulted in death.Internet of things(IoT)and health monitoring sensors have improved the medical care systems by enabling latency-sensitive surveillance and computing of large amounts of patients’data.The major challenge being faced currently in this problem is its limited scalability and late detection of cardiovascular events in IoT-based computing environments.To this end,this paper proposes a novel framework to early detection of cardiovascular events based on a deep learning architecture in IoT environments.Experimental results showed that the proposed method was able to detect cardiovascular events with better performance(95.30%average sensitivity and 95.94%mean prediction values).
基金This research was financially supported by the Ministry of Trade,Industry,and Energy(MOTIE),Korea,under the“Project for Research and Development with Middle Markets Enterprises and DNA(Data,Network,AI)Universities”(AI-based Safety Assessment and Management System for Concrete Structures)(ReferenceNumber P0024559)supervised by theKorea Institute for Advancement of Technology(KIAT).
文摘Time-series data provide important information in many fields,and their processing and analysis have been the focus of much research.However,detecting anomalies is very difficult due to data imbalance,temporal dependence,and noise.Therefore,methodologies for data augmentation and conversion of time series data into images for analysis have been studied.This paper proposes a fault detection model that uses time series data augmentation and transformation to address the problems of data imbalance,temporal dependence,and robustness to noise.The method of data augmentation is set as the addition of noise.It involves adding Gaussian noise,with the noise level set to 0.002,to maximize the generalization performance of the model.In addition,we use the Markov Transition Field(MTF)method to effectively visualize the dynamic transitions of the data while converting the time series data into images.It enables the identification of patterns in time series data and assists in capturing the sequential dependencies of the data.For anomaly detection,the PatchCore model is applied to show excellent performance,and the detected anomaly areas are represented as heat maps.It allows for the detection of anomalies,and by applying an anomaly map to the original image,it is possible to capture the areas where anomalies occur.The performance evaluation shows that both F1-score and Accuracy are high when time series data is converted to images.Additionally,when processed as images rather than as time series data,there was a significant reduction in both the size of the data and the training time.The proposed method can provide an important springboard for research in the field of anomaly detection using time series data.Besides,it helps solve problems such as analyzing complex patterns in data lightweight.
文摘Epidemiological studies showed the incidence mortality rates of cancer were increasing in recent decades in Chinese population.National and regional preventive programs aim to reduce the health hazards of cancer and focuse the population at high risks for specific cancer, particularly in rural areas and to offer the access to early detection for multlple cancers in urban areas. The early screening, early detection and treatment have been put into operation for the population at risks in rural areas at first, and in the urban areas in recent years. To understand the epidemic patterns and trends of cancer, and the experiences in applying early detection strategies in China, selected literatures were reviewed for brief summary.
基金Supported by Henan Province science and Technology Research Projects,No.162102310041National Key R&D Program of China,No.2016YFC0106604National Natural Science Foundation of China,No.81502591
文摘AIM To investigate the value of multiparameter joint analysis in the early diagnosis of gastric cancer(GC) in clinical practice.METHODS Concentrations of CEA, CA724 and three kinds of cytokines(TNF-α, IL-6 and IL-8) in 176 GC patients, 117 atypical hyperplasia patients, and 204 healthy control individuals were used for building the diagnostic model, then 58 GC patients, 41 atypical hyperplasia patients, and 66 healthy control individuals were enrolled independently. The joints of the indicators were analyzed by binary logistic regression analysis method.RESULTS For discriminating the healthy control group and the GC group, IL-6 had the best diagnostic value, and the area under curve(AUC) of joint analysis was 0.95(0.93-0.97). For the early stage and advanced stage GC, the AUC were 0.95(0.92-0.98) and 0.95(0.92-0.97). For discriminating the atypical hyperplasia group and GC group, CA724 had the best diagnostic value, and the AUC of joint analysis was 0.97(0.95-0.99). For the early stage and advanced stage GC groups, the AUC were 0.98(0.96-0.99) and 0.96(0.94-0.98). After evaluation, for discriminating the GC, early stage GC and advanced cancer group from the healthy control group, the diagnostic sensitivity was 89.66%, 84.21% and 92.31%, respectively, and the specificity was 92.42%, 90.91% and 90.91%. For discriminating the GC, early stage GC and advanced cancer groups from the atypical hyperplasia group, the diagnostic sensitivity was 87.93%, 78.95% and 92.31%, respectively, and the specificity was 87.80%, 85.37% and 90.24%.CONCLUSION We have built a diagnostic model including CEA, CA724, IL-6, IL-8, and TNF-α. It may provide potential assistance as a screening method for the early detection of GC.
文摘This review article summarizes the research advances of the plasma-based SEPT9 gene methylation assay for the clinical detection of colorectal cancer and its limitations. Colorectal cancer is a common malignancy with a poor prognosis and a high mortality, for which early detection and diagnosis are particularly crucial for the high-risk groups. Increasing evidence supported that SEPT9 gene methylation is associated with the pathogenesis of colorectal cancer and that detecting the level of methylation of SEPT9 in the peripheral blood can be used for screening of colorectal cancer in susceptible populations. In recent years, the data obtained in clinical studies demonstrated that the SEPT9 gene methylation assay has a good diagnostic performance with regard to both sensitivity and specificity with the advantage of better acceptability, convenience and compliance with serological testing compared with fecal occult blood tests and carcinoembryonic antigen for colorectal cancer(CRC). Furthermore, the combination of multiple methods or markers has become a growing trend for CRC detection and screening. Nevertheless, the clinical availability of the methylated SEPT9 assay is still limited because of the large degree of sample heterogeneity caused by demographic characteristics, pathological features, comorbidities and/or technique selection. Another factor is the cost-effectiveness of colorectal cancer screening strategies that hinders its large-scale application. In addition, improvements in its accuracy in detecting adenomas and premalignant polyps are required.
基金Supported by Youth Foundation of Shanghai Municipal Health Bureau(in part),No.122Young Teachers Program of Shanghai University,National Natural Science Foundation of China,No.81302087Natural Science Foundation of Shanghai,No.13ZR1457400
文摘Pancreatic ductal adenocarcinoma(PDAC) is one of the most lethal forms of cancer. Substantial progress has been made in the understanding of the biology of pancreatic cancer, and advances in patient management have been significant. However, most patients(nearly80%) who present with locally advanced or metastatic disease have an extremely poor prognosis. Survival is better for those with malignant disease localized to the pancreas, because surgical resection at present offers the only chance of cure. Therefore, the early detection of pancreatic cancer may benefit patients with PDAC.However, its low rate of incidence and the limitations of current screening strategies make early detection difficult. Recent advances in the understanding of the pathogenesis of PDAC suggest that it is possible to detect PDAC in early stages and even identify precursor lesions. The presence of new-onset diabetes mellitus in the early phase of pancreatic cancer may provide cluesfor its early diagnosis. Advances in the identification of novel circulating biomarkers including serological signatures, autoantibodies, epigenetic markers, circulating tumor cells and microRNAs suggest that they can be used as potential tools for the screening of precursors and early stage PDAC in the future. However, proper screening strategies based on effective screening methodologies need to be tested for clinical application.
基金National Key R&D Program of China,No.2016YFC0106604National Natural Science Foundation of China,No.81471761 and No.81501568
文摘AIM In our previous study, we have built a nine-gene(GPC3, HGF, ANXA1, FOS, SPAG9, HSPA1 B, CXCR4, PFN1, and CALR) expression detection system based on the Ge XP system. Based on peripheral blood and Ge XP, we aimed to analyze the results of genes expression by different multi-parameter analysis methods and build a diagnostic model to classify hepatocellular carcinoma(HCC) patients and healthy people.METHODS Logistic regression analysis, discriminant analysis, classification tree analysis, and artificial neural network were used for the multi-parameter gene expression analysis method. One hundred and three patients with early HCC and 54 age-matched healthy normal controls were used to build a diagnostic model. Fiftytwo patients with early HCC and 34 healthy people were used for validation. The area under the curve, sensitivity, and specificity were used as diagnostic indicators.RESULTS Artificial neural network of the total nine genes had the best diagnostic value, and the AUC, sensitivity, and specificity were 0.943, 98%, and 85%, respectively. At last, 52 HCC patients and 34 healthy normal controls were used for validation. The sensitivity and specificity were 96% and 86%, respectively.CONCLUSION Multi-parameter analysis methods may increase the diagnostic value compared to single factor analysis and they may be a trend of the clinical diagnosis in the future.
基金This study was supported by the China National Science Foundation(Grant Nos.82022048 and 81871893)the Key Project of Guangzhou Scientific Research Project(Grant No.201804020030).
文摘Lung cancer is associated with a heavy cancer-related burden in terms of patients’physical and mental health worldwide.Two randomized controlled trials,the US-National Lung Screening Trial(NLST)and Nederlands-Leuvens Longkanker Screenings Onderzoek(NELSON),indicated that low-dose CT(LDCT)screening results in a statistically significant decrease in mortality in patients with lung cancer,LDCT has become the standard approach for lung cancer screening.However,many issues in lung cancer screening remain unresolved,such as the screening criteria,high false-positive rate,and radiation exposure.This review first summarizes recent studies on lung cancer screening from the US,Europe,and Asia,and discusses risk-based selection for screening and the related issues.Second,an overview of novel techniques for the differential diagnosis of pulmonary nodules,including artificial intelligence and molecular biomarker-based screening,is presented.Third,current explorations of strategies for suspected malignancy are summarized.Overall,this review aims to help clinicians understand recent progress in lung cancer screening and alleviate the burden of lung cancer.
文摘AIM:To evaluate the difference in diagnostic performance of hydro-stomach computed tomography(CT) to detect early gastric cancer(EGC) between blinded and unblinded analysis and to assess independent factors affecting visibility of cancer foci.METHODS:Two radiologists initially blinded and then unblinded to gastroscopic and surgical-histological findings independently reviewed hydro-stomach CT images of 110 patients with single EGC.They graded the visibility of cancer foci for each of three gastric segments(upper,middle and lower thirds) using a 4-point scale(1:definitely absent,2:probably absent,3:probably present,and 4:definitely present).The sensitivity and specificity for detecting an EGC were calculated.Intraobserver and interobserver agreements were analyzed.The visibility of an EGC was evaluated with regard to tumor size,invasion depth,gastric segments,histological type and gross morphology using univariate and multivariate analysis.RESULTS:The respective sensitivities and specificities [reviewer 1:blinded,20%(22/110) and 98%(215/220);unblinded,27%(30/110) and 100%(219/220)/reviewer 2:blinded,19%(21/110) and 98%(216/220);unblinded,25%(27/110) and 98%(215/220)] were not significantly different.Although intraobserver agreements were good(weighted κ = 0.677 and 0.666),interobserver agreements were fair(blinded,0.371) or moderate(unblinded,0.558).For both univariate and multivariate analyses,the tumor size and invasion depth were statistically significant factors affecting visibility.CONCLUSION:The diagnostic performance of hydrostomach CT to detect an EGC was not significantly different between blinded and unblinded analysis.The tumor size and invasion depth were independent factors for visibility.
基金supported by TATA Consultancy Servies(TCS)Research Fellowship Program,India
文摘Wi-Fi devices have limited battery life because of which conserving battery life is imperative. The 802.11 Wi-Fi standard provides power management feature that allows stations(STAs) to enter into sleep state to preserve energy without any frame losses. After the STA wakes up, it sends a null data or PS-Poll frame to retrieve frame(s) buffered by the access point(AP), if any during its sleep period. An attacker can launch a power save denial of service(PS-DoS) attack on the sleeping STA(s) by transmitting a spoofed null data or PS-Poll frame(s) to retrieve the buffered frame(s) of the sleeping STA(s) from the AP causing frame losses for the targeted STA(s). Current approaches to prevent or detect the PS-DoS attack require encryption,change in protocol or installation of proprietary hardware. These solutions suffer from expensive setup, maintenance, scalability and deployment issues. The PS-DoS attack does not differ in semantics or statistics under normal and attack circumstances.So signature and anomaly based intrusion detection system(IDS) are unfit to detect the PS-DoS attack. In this paper we propose a timed IDS based on real time discrete event system(RTDES) for detecting PS-DoS attack. The proposed DES based IDS overcomes the drawbacks of existing systems and detects the PS-DoS attack with high accuracy and detection rate. The correctness of the RTDES based IDS is proved by experimenting all possible attack scenarios.
文摘To review the present status of breast cancer(BC) screening/early detection in low- and middle-income countries(LMICs) and identify the way forward, an open focused search for articles was undertaken in Pub Med, Google Scholar and Google, and using a snowball technique, further articles were obtained from the reference list of initial search results. In addition, a query was put up on Research Gate to obtain more references and find out the general opinion of experts on the topic. Experts were also personally contacted for their opinion. Breast cancer(BC) is the most common cancer in women in the world. The rise in incidence is highest in LMICs where the incidence has often been much lower than high-income countries. In spite of more women dying of cancer than pregnancy or childbirth related causes in LMICs, most of the focus and resources are devoted to maternal health. Also, the majority of women in LMICs present at late stages to a hospital to initiate treatment. A number of trials have been conducted in various LMICs regarding the use of clinical breast examination and mammography in various combinations to understand the best ways of implementing a population level screening/early detection of BC; nevertheless, more research in this area is badly needed for different LMIC specific contexts. No-tably, very few LMICs have national level programs for BC prevention via screening/early detection and even stage reduction is not on the public health agenda. This is in addition to other barriers such as lack of awareness among women regarding BC and the presence of stigma, inappropriate attitudes and lack of following proper screening behavior, such as conducting breast self-examinations. The above is mixed with the apathy and lack of awareness of policy makers regarding the fact that BC prevention is much more cost-effective and humane than BC treatment. Implementation of population level programs for screening/early detection of BC, along with use of ways to improve awareness of women regarding BC, can prove critical in stemming the increasing burden of BC in LMICs. Use of newer modalities such as ultrasonography which is more suited to LMIC populations and use of m Health for awareness creation and increasing screening compliance are much needed extra additions to the overall agenda of LMICs in preventing BC.