Congruent Feature Selection Method to Improve the Efficacy of Machine Learning-Based Classification in Medical Image Processing

Machine learning(ML)is increasingly applied for medical image processing with appropriate learning paradigms.These applications include analyzing images of various organs,such as the brain,lung,eye,etc.,to identify specific flaws/diseases for diagnosis.The primary concern of ML applications is the precise selection of flexible image features for pattern detection and region classification.Most of the extracted image features are irrelevant and lead to an increase in computation time.Therefore,this article uses an analytical learning paradigm to design a Congruent Feature Selection Method to select the most relevant image features.This process trains the learning paradigm using similarity and correlation-based features over different textural intensities and pixel distributions.The similarity between the pixels over the various distribution patterns with high indexes is recommended for disease diagnosis.Later,the correlation based on intensity and distribution is analyzed to improve the feature selection congruency.Therefore,the more congruent pixels are sorted in the descending order of the selection,which identifies better regions than the distribution.Now,the learning paradigm is trained using intensity and region-based similarity to maximize the chances of selection.Therefore,the probability of feature selection,regardless of the textures and medical image patterns,is improved.This process enhances the performance of ML applications for different medical image processing.The proposed method improves the accuracy,precision,and training rate by 13.19%,10.69%,and 11.06%,respectively,compared to other models for the selected dataset.The mean error and selection time is also reduced by 12.56%and 13.56%,respectively,compared to the same models and dataset.

Relationship between the use of smart medical services and mental health status

In this editorial,I comment on the article by Zhang et al.To emphasize the importance of the topic,I discuss the relationship between the use of smart medical devices and mental health.Smart medical services have the potential to positively influence mental health by providing monitoring,insights,and inter-ventions.However,they also come with challenges that need to be addressed.Understanding the primary purpose for which individuals use these smart tech-nologies is essential to tailoring them to specific mental health needs and prefe-rences.

Getting physical with medical education:Exercise based virtual anatomy review classes for medical students

The benefits of regular physical activity are well known.Yet,few studies have examined the effectiveness of integrating physical activity(PA)into curricula within a post-secondary setting.To investigate the incorporation of PA into medical curriculum,we developed a series of optional exercise-based review sessions designed to reinforce musculoskeletal(MSK)anatomy course material.These synchronous sessions were co-taught by a group fitness instructor and an anatomy instructor.The fitness instructor would lead students through both strength and yoga style exercises,while the anatomy instructor asked questions about relevant anatomical structures related to course material previously covered.After the sessions,participants were asked to evaluate the classes on their self-reported exam preparedness in improving MSK anatomy knowledge,PA levels,and mental wellbeing.Thirty participants completed surveys;a majority agreed that the classes increased understanding of MSK concepts(90.0%)and activity levels(97.7%).Many(70.0%)felt that the classes helped reduce stress.The majority of respondents(90.0%)agreed that the classes contributed to increased feelings of social connectedness.Overall,medical students saw benefit in PA based interventions to supplement MSK course concepts.Along with increasing activity levels and promoting health behaviours,integrating PA into medical curriculum may improve comprehension of learning material,alleviate stress and foster social connectivity among medical students.

Curved Spine:The Shape of Spine in Taoist Body Diagrams and Its Influence on Medical Body Diagrams

From the early Taoist diagrams of the human body to the end of the Qing dynasty and the beginning of the Republic of China,Taoists exaggerated and deformed the human spine in a shape-shifting manner.It is likely that medical practitioners were influenced by this style of representation,and there are also numerous diagrams of the human body with the curved spine in the lateral-view diagrams of viscera and Ming Tang Tu(明堂图Acupuncture and Moxibustion Chart),which constantly show the human torso in an elliptical“egg shape”.No later than the Ming dynasty,medical practitioners began to depict the actual physiological spinal curve of the human body.By the Qing dynasty,the depiction of the spinal curve in medical diagrams of the human figure showed a tendency to part ways with the Taoist freehand style of the previous generation.Although the representation of the curve of the spine was very crude,later medical images of the human body at least gradually straightened the spine and no longer depicted it in a shape-shifting manner.However,the curved spine in Taoist diagrams of the human body continued to exist,and the presentation of the curved spine never changed.This way of depicting its appearance,which is very different from reality,is shaped by Taoism's special way of perceiving and viewing the body,and may also contain another form of truth.

Blockchain-Assisted Electronic Medical Data-Sharing:Developments,Approaches and Perspectives

Medical blockchain data-sharing is a technique that employs blockchain technology to facilitate the sharing of electronic medical data.The blockchain is a decentralized digital ledger that ensures data-sharing security,transparency,and traceability through cryptographic technology and consensus algorithms.Consequently,medical blockchain data-sharing methods have garnered significant attention and research efforts.Nevertheless,current methods have different storage and transmission measures for original data in the medical blockchain,resulting in large differences in performance and privacy.Therefore,we divide the medical blockchain data-sharing method into on-chain sharing and off-chain sharing according to the original data storage location.Among them,off-chain sharing can be subdivided into on-cloud sharing and local sharing according to whether the data is moved.Subsequently,we provide a detailed analysis of basic processes and research content for each method.Finally,we summarize the challenges posed by the current methods and discuss future research directions.

Secure approach to sharing digitized medical data in a cloud environment

Without proper security mechanisms, medical records stored electronically can be accessed more easily than physical files. Patient health information is scattered throughout the hospital environment, including laboratories, pharmacies, and daily medical status reports. The electronic format of medical reports ensures that all information is available in a single place. However, it is difficult to store and manage large amounts of data. Dedicated servers and a data center are needed to store and manage patient data. However, self-managed data centers are expensive for hospitals. Storing data in a cloud is a cheaper alternative. The advantage of storing data in a cloud is that it can be retrieved anywhere and anytime using any device connected to the Internet. Therefore, doctors can easily access the medical history of a patient and diagnose diseases according to the context. It also helps prescribe the correct medicine to a patient in an appropriate way. The systematic storage of medical records could help reduce medical errors in hospitals. The challenge is to store medical records on a third-party cloud server while addressing privacy and security concerns. These servers are often semi-trusted. Thus, sensitive medical information must be protected. Open access to records and modifications performed on the information in those records may even cause patient fatalities. Patient-centric health-record security is a major concern. End-to-end file encryption before outsourcing data to a third-party cloud server ensures security. This paper presents a method that is a combination of the advanced encryption standard and the elliptical curve Diffie-Hellman method designed to increase the efficiency of medical record security for users. Comparisons of existing and proposed techniques are presented at the end of the article, with a focus on the analyzing the security approaches between the elliptic curve and secret-sharing methods. This study aims to provide a high level of security for patient health records.

Factors Affecting Cotrimoxazole Prophylactic Therapy Compliance in HIV Patients Attending a Care and Treatment Clinic at Bugando Medical Centre in Mwanza, Tanzania

Introduction: Cotrimoxazole Prophylactic Therapy (CPT) compliance lowers the risk of opportunistic infections and other Acquired Immune Deficiency Syndrome (AIDS)-related diseases. The aim of this study was to examine factors that influence compliance with CPT among HIV patients in the Care and Treatment Clinic (CTC) at Bugando Medical Centre (BMC) in Mwanza, Tanzania. Methods: A descriptive cross-sectional study was conducted at the BMC between April 1, 2021, and June 30, 2021. Data were collected using face-to-face interviews and a semi-structured questionnaire. Data are presented in frequency, percentages, and cross-tabulation tables. A P-value of less than 0.05 was considered statistically significant. Results: The prevalence of compliance with CPT by self-reported measurement was 158 (63.7%). Most CPT-compliant participants were more likely to have a spouse who is familiar with CPT, have a family member who is aware of their HIV status, and be aware of the benefits of CPT. The majority of participants who complied with CPT were more likely to have experienced counseling during refill, felt that the length of time spent seeing doctors for treatment was reasonable, and received accurate information from them. Conclusion: Most adult HIV patients attending CTC at BMC were reported to be in compliance with CPT. These findings suggest that improving social support and patient-provider communication may be effective strategies for improving compliance with CPT among HIV patients.

Regulatory gaps in India’s medical device framework:The case of Johnson and Johnson’s faulty hip implants

The Johnson and Johnson faulty hip implant case represents one of the most significant crises in medical device history,impacting nearly 93000 patients worldwide.In response to alarming failure rates and a global recall in August 2010,countries such as Australia,the United States,and the United Kingdom quickly implemented revision surgeries and reimbursement programs to protect patient safety.In stark contrast,India's response was alarmingly delayed;defective implants continued to be sold even after the global recall.By the time the import license was revoked,and the Central Drugs Standard Control Organization issued a recall notice,these implants had already been involved in 4700 surgeries across India.This paper explores the systemic weaknesses in India’s medical device regulatory framework that contributed to this delayed action,resulting in many patients suffering from serious health complications.It highlights deficiencies in monitoring and reporting mechanisms,inadequate regulatory oversight,and insufficient approval processes.Furthermore,the inability to trace affected patients and provide necessary compensation underscores significant gaps in regulation.Although subsequent legislative reforms were introduced,this paper argues that substantial loopholes remain,posing risks for future incidents.Thus,urgent,comprehensive,and enforceable regulatory measures are needed to increase patient safety.

Willingness to Pay for Antiretroviral Drugs Covered by Medical Insurance among People Living with HIV in 18 Chinese Cities

Objective Antiretroviral drugs covered by medical insurance have been gradually used by people living with human immunodeficiency virus(PLWH)in recent years in China.This study aimed to analyze their willingness to pay(WTP)for antiretroviral drugs.Methods A mixed-methods study design involving a cross-sectional survey and in-depth interviews was conducted.A cross-sectional survey was performed to collect data on the general characteristics,economic status,antiretroviral therapy(ART)status,and WTP of PLWH in 18 Chinese cities from August 2022 to February 2023.Multivariate logistic regression was used to analyze the factors associated with WTP.Representatives of PLWH were interviewed via in-depth interviews,and the data were thematically analyzed.Results Among the 941 PLWH,271(28.80%)were willing to pay for antiretroviral drugs covered by medical insurance.For basic medical insurance for urban and rural residents,PLWH with the following characteristics were more willing to pay:an educational level of senior high school or technical secondary school,having an undergraduate degree or higher,frequently working away from their hometowns,and homosexual transmission.Off-farm workers and recipients of government medical aid were more unwilling to pay.For basic medical insurance for urban employees,PLWH with the following characteristics were more willing to pay:frequently working away from their hometowns;homosexual transmission;personal annual income≥100,000 CNY;and adverse events of antiretroviral drugs.The main reasons for PLWH’s WTP for antiretroviral drugs covered by medical insurance were that the drugs had fewer adverse events and were easier to administer.The main reasons for PLWH’s unwillingness to pay were financial difficulties and privacy concerns.Conclusion Nearly one-third of PLWH are willing to pay for antiretroviral drugs covered by medical insurance.In the future,PLWH with a high WTP can be guided to use these drugs.

Privacy-Preserving Healthcare and Medical Data Collaboration Service System Based on Blockchain and Federated Learning

As the volume of healthcare and medical data increases from diverse sources,real-world scenarios involving data sharing and collaboration have certain challenges,including the risk of privacy leakage,difficulty in data fusion,low reliability of data storage,low effectiveness of data sharing,etc.To guarantee the service quality of data collaboration,this paper presents a privacy-preserving Healthcare and Medical Data Collaboration Service System combining Blockchain with Federated Learning,termed FL-HMChain.This system is composed of three layers:Data extraction and storage,data management,and data application.Focusing on healthcare and medical data,a healthcare and medical blockchain is constructed to realize data storage,transfer,processing,and access with security,real-time,reliability,and integrity.An improved master node selection consensus mechanism is presented to detect and prevent dishonest behavior,ensuring the overall reliability and trustworthiness of the collaborative model training process.Furthermore,healthcare and medical data collaboration services in real-world scenarios have been discussed and developed.To further validate the performance of FL-HMChain,a Convolutional Neural Network-based Federated Learning(FL-CNN-HMChain)model is investigated for medical image identification.This model achieves better performance compared to the baseline Convolutional Neural Network(CNN),having an average improvement of 4.7%on Area Under Curve(AUC)and 7%on Accuracy(ACC),respectively.Furthermore,the probability of privacy leakage can be effectively reduced by the blockchain-based parameter transfer mechanism in federated learning between local and global models.

Reliable Data Collection Model and Transmission Framework in Large-Scale Wireless Medical Sensor Networks

Large-scale wireless sensor networks(WSNs)play a critical role in monitoring dangerous scenarios and responding to medical emergencies.However,the inherent instability and error-prone nature of wireless links present significant challenges,necessitating efficient data collection and reliable transmission services.This paper addresses the limitations of existing data transmission and recovery protocols by proposing a systematic end-to-end design tailored for medical event-driven cluster-based large-scale WSNs.The primary goal is to enhance the reliability of data collection and transmission services,ensuring a comprehensive and practical approach.Our approach focuses on refining the hop-count-based routing scheme to achieve fairness in forwarding reliability.Additionally,it emphasizes reliable data collection within clusters and establishes robust data transmission over multiple hops.These systematic improvements are designed to optimize the overall performance of the WSN in real-world scenarios.Simulation results of the proposed protocol validate its exceptional performance compared to other prominent data transmission schemes.The evaluation spans varying sensor densities,wireless channel conditions,and packet transmission rates,showcasing the protocol’s superiority in ensuring reliable and efficient data transfer.Our systematic end-to-end design successfully addresses the challenges posed by the instability of wireless links in large-scaleWSNs.By prioritizing fairness,reliability,and efficiency,the proposed protocol demonstrates its efficacy in enhancing data collection and transmission services,thereby offering a valuable contribution to the field of medical event-drivenWSNs.

Relationship between pancreatic morphological changes and diabetes in autoimmune pancreatitis:Multimodal medical imaging assessment has important potential

Autoimmune pancreatitis(AIP)is a special type of chronic pancreatitis with cli-nical symptoms of obstructive jaundice and abdominal discomfort;this condition is caused by autoimmunity and marked by pancreatic fibrosis and dysfunction.Previous studies have revealed a close relationship between early pancreatic atrophy and the incidence rate of diabetes in type 1 AIP patients receiving steroid treatment.Shimada et al performed a long-term follow-up study and reported that the pancreatic volume(PV)of these patients initially exponentially decreased but then slowly decreased,which was considered to be an important factor related to diabetes;moreover,serum IgG4 levels were positively correlated with PV during follow-up.In this letter,regarding the original study presented by Shimada et al,we present our insights and discuss how multimodal medical imaging and arti-ficial intelligence can be used to better assess the relationship between pancreatic morphological changes and diabetes in patients with AIP.

Associative Tasks Computing Offloading Scheme in Internet of Medical Things with Deep Reinforcement Learning

The Internet of Medical Things(Io MT) is regarded as a critical technology for intelligent healthcare in the foreseeable 6G era. Nevertheless, due to the limited computing power capability of edge devices and task-related coupling relationships, Io MT faces unprecedented challenges. Considering the associative connections among tasks, this paper proposes a computing offloading policy for multiple-user devices(UDs) considering device-to-device(D2D) communication and a multi-access edge computing(MEC)technique under the scenario of Io MT. Specifically,to minimize the total delay and energy consumption concerning the requirement of Io MT, we first analyze and model the detailed local execution, MEC execution, D2D execution, and associated tasks offloading exchange model. Consequently, the associated tasks’ offloading scheme of multi-UDs is formulated as a mixed-integer nonconvex optimization problem. Considering the advantages of deep reinforcement learning(DRL) in processing tasks related to coupling relationships, a Double DQN based associative tasks computing offloading(DDATO) algorithm is then proposed to obtain the optimal solution, which can make the best offloading decision under the condition that tasks of UDs are associative. Furthermore, to reduce the complexity of the DDATO algorithm, the cacheaided procedure is intentionally introduced before the data training process. This avoids redundant offloading and computing procedures concerning tasks that previously have already been cached by other UDs. In addition, we use a dynamic ε-greedy strategy in the action selection section of the algorithm, thus preventing the algorithm from falling into a locally optimal solution. Simulation results demonstrate that compared with other existing methods for associative task models concerning different structures in the Io MT network, the proposed algorithm can lower the total cost more effectively and efficiently while also providing a tradeoff between delay and energy consumption tolerance.

Ultrasound in Ti-Rads Classification of Thyroid Nodules at the Marie Curie Medical Clinic

Introduction: A thyroid nodule is a localized hypertrophy within the thyroid parenchyma. The aim of our study was to study the benefit of ultrasound in the Ti-rads classification of thyroid nodules. Methodology: This was a prospective study with a descriptive aim, with prospective collection, which took place over a period of 17 months at the “Marie Curie” medical clinic. The ultrasound machine used was a Voluson E8 from 2011 and the examinations were carried out by two radiologists and two experienced sonographers. The parameters studied were sociodemographic data;clinical data and ultrasound aspects of the Ti-rads classification in the management of nodules. Results: We collected 235 patients out of 738 patients referred to the service for a cervical ultrasound, i.e. a frequency of 31.84% of cases. There was a female predominance with 95.7% of cases and a sex ratio of 0.04. The average age of our patients was 50 years. We found on cervical ultrasound: Isthmo-lobar glandular hyperplasia in 99 patients, i.e. a frequency of 42.1%. The Ti-rads 3 classification was the most represented in 69.4% of cases. The benignity criterion represented 85.6% of cases in our patients and the malignancy criterion represented 14.4% of cases. Conclusion: The precise description of a thyroid nodule provided by ultrasound (Ti-rads) is essential in the management of nodules.

Teaching Reform and Practice of Functional Experiment Based on the Cultivation of Excellent Medical Talents

In order to cultivate excellent clinical medical talents with a solid foundation, strong literacy, refined skills, excellent communication abilities, innovative thinking, and a strong focus on practicality, functional experiments have undergone a series of reforms in areas such as constructing new curriculum systems, improving teaching content, updating teaching equipment, introducing new teaching models, and enhancing teaching evaluation systems.

Health performance assessment modeling and its application to compact medical communities in China

Some regions in China have already implemented capitation payment or capitation budget management for medical insurance funds.However,there remains a shortage of adequate tools and methodologies to accurately quantify differences in population health risks.Therefore,this paper constructs a health performance assessment model that comprises four steps.The first step is to categorize all participants into health risk groups based on whether they have contracted with a family doctor,their age,sex,and the type of consultation.The second step is to categorize health risk groups based on differences in healthcare resource utilization.The third step is to analyze health performance by examining healthcare resource utilization year over year.The fourth step is to apply the assessment results to assist local finance bureaus and medical insurance bureaus in developing incentive schemes.According to cost weights,the health risk groups are split into six classes:insured residents without health care visits,healthy insured person,slightly ill insured patients,ill insured patients,more seriously disease patients,and severely ill insured patients.We evaluate one compact medical community's health performance by examining changes in the proportion of resource usage group size and expense.From 2019 to 2021,both the proportion of patients with severe and ultra‐severe diseases and the proportion of costs in the sample increased,according to changes in resource utilization levels.This result indicates that the population's overall health has not improved and that the compact medical community is still primarily focused on treating diseases,with poor implementation of health maintenance measures and minimal improvement in health performance.

Research on Teaching Reform of Basic Medical Courses in Comprehensive Universities Oriented Towards“Clinical Competency”

Through this study,we aim to construct a teaching model for basic medical courses that enhances“clinical competency.”We explore the optimal methods and pathways for the organic integration of exam-oriented teaching and professional teaching,optimize teaching efficiency,improve teaching quality and educational effectiveness,and provide theoretical support for the cultivation of clinical medical talents in China.The goal is to establish a talent cultivation objective oriented towards“clinical competency,”promote the teaching reform of basic medical courses in comprehensive universities,facilitate the transition of basic medical course teaching from“teacher knowledge presentation”to“student knowledge construction,”and cultivate high-quality medical talents with clinical competency.

A Study on the Impact of Psychological Counseling for Minor Medical Students in Clinical Teaching and Learning

Objective:To explore the impact of psychological counseling for underage medical students in clinical teaching.Methods:24 of the 48 underage medical students who were interned in our hospital from March 2023 to February 2024 were randomly selected to adopt the teaching management method of one-on-one psychological guidance as the observation group;the remaining 24 adopted the traditional teaching management method as the control group.The observation of the effects of psychological detachment on various aspects of underage medical students allows the determination of whether psychological detachment impacts clinical teaching.Results:The observation group’s theoretical examination scores,skill assessment scores,and departmental performance evaluation scale score excellence rate were higher than the control group’s,with P<0.05 being statistically significant.At the same time,the clinical teaching and teaching management ability of the hospital was also improved.Conclusion:Psychological guidance for underage medical students can not only improve the comprehensive quality of medical students but also improve the teaching level,which is conducive to improving the teaching effect,and it is a clinical teaching mode worth promoting.

Adapter Based on Pre-Trained Language Models for Classification of Medical Text

We present an approach to classify medical text at a sentence level automatically.Given the inherent complexity of medical text classification,we employ adapters based on pre-trained language models to extract information from medical text,facilitating more accurate classification while minimizing the number of trainable parameters.Extensive experiments conducted on various datasets demonstrate the effectiveness of our approach.

Meta-Analysis of Efficacy and Safety of Mongolian Medical Warm Acupuncture in the Treatment of Lumbar Disc Herniation

Objective:To systematically evaluate the safety and efficacy of Mongolian medical warm acupuncture in the treatment of lumbar disc herniation(LDH).Methods:CNKI,Wanfang,VIP,Pubmed,Embase,Cochrane Library,and other databases were searched.The randomized controlled trials(RCTs)on the treatment of LDH with Mongolian medical warm acupuncture were manually searched in the Chinese Journal of Ethnic Medicine,Chinese Journal of Mongolian Medicine,Journal of Inner Mongolia University for Nationalities,and Journal of Inner Mongolia Medical University.The search time limit was from January 2000 to October 2023.RevMan5.4 software was used to analyze the included and excluded literature.Results:A total of 8 RCTs involving 1,042 patients with LDH were included,with 551 patients in the observation group and 491 patients in the control group.The results of the meta-analysis showed that a total of 8 randomized controlled trials were included in the treatment of LDH with Mongolian medical warm acupuncture compared with simple acupuncture(RR=1.18,95%CI=[1.12,1.23],P<0.00001).Conclusion:The total effective rate of Mongolian medical warm acupuncture for LDH is higher than that of simple acupuncture.However,due to the low quality of the literature included in this study,multi-dimensional,large sample size,and more rigorous clinical randomized trials are needed for further verification in the future.