Experts' Knowledge Fusion in Model-Based Diagnosis Based on Bayes Networks

In previous researches on a model-based diagnostic system, the components are assumed mutually independent. Howerver , the assumption is not always the case because the information about whether a component is faulty or not usually influences our knowledge about other components. Some experts may draw such a conclusion that 'if component m 1 is faulty, then component m 2 may be faulty too'. How can we use this experts' knowledge to aid the diagnosis? Based on Kohlas's probabilistic assumption-based reasoning method, we use Bayes networks to solve this problem. We calculate the posterior fault probability of the components in the observation state. The result is reasonable and reflects the effectiveness of the experts' knowledge.

Movement analysis in the diagnosis and management of Parkinson’s disease

Challenges in the diagnosis and treatment of Parkinson’s disease:Parkinson’s disease(PD)is an increasingly prevalent neurodegenerative disease,at first sight primarily characterized by motor symptoms,although non-motor symptoms also constitute a major part of the overall phenotype.Clinically,this disease cannot be diagnosed reliably until a large part of the vulnerable dopaminergic neurons has been irretrievably lost,and the disease progresses inexorably.New biological criteria for PD have been proposed recently and might eventually improve early diagnosis,but they require further validation,and their use will initially be restricted to a research environment(Darweesh et al.,2024).

Visualizing traumatic brain injury:ocular clues for diagnosis and assessment

Traumatic brain injury (TBI) is defined as damage to the brain resulting from an external sudden physical force or shock to the head.It is considered a silent public health epidemic causing significant death and disability globally.There were 64,000 TBI related deaths reported in the USA in 2020,with about US$76 billion in direct and indirect medical costs annually.

Pathogenesis, diagnosis, and treatment of epilepsy: electromagnetic stimulation-mediated neuromodulation therapy and new technologies

Epilepsy is a severe,relapsing,and multifactorial neurological disorder.Studies regarding the accurate diagnosis,prognosis,and in-depth pathogenesis are crucial for the precise and effective treatment of epilepsy.The pathogenesis of epilepsy is complex and involves alterations in variables such as gene expression,protein expression,ion channel activity,energy metabolites,and gut microbiota composition.Satisfactory results are lacking for conventional treatments for epilepsy.Surgical resection of lesions,drug therapy,and non-drug interventions are mainly used in clinical practice to treat pain associated with epilepsy.Non-pharmacological treatments,such as a ketogenic diet,gene therapy for nerve regeneration,and neural regulation,are currently areas of research focus.This review provides a comprehensive overview of the pathogenesis,diagnostic methods,and treatments of epilepsy.It also elaborates on the theoretical basis,treatment modes,and effects of invasive nerve stimulation in neurotherapy,including percutaneous vagus nerve stimulation,deep brain electrical stimulation,repetitive nerve electrical stimulation,in addition to non-invasive transcranial magnetic stimulation and transcranial direct current stimulation.Numerous studies have shown that electromagnetic stimulation-mediated neuromodulation therapy can markedly improve neurological function and reduce the frequency of epileptic seizures.Additionally,many new technologies for the diagnosis and treatment of epilepsy are being explored.However,current research is mainly focused on analyzing patients’clinical manifestations and exploring relevant diagnostic and treatment methods to study the pathogenesis at a molecular level,which has led to a lack of consensus regarding the mechanisms related to the disease.

MicroRNAs as potential biomarkers for diagnosis of post-traumatic stress disorder

Post-traumatic stress disorder is a mental disorder caused by exposure to severe traumatic life events.Currently,there are no validated biomarkers or laboratory tests that can distinguish between trauma survivors with and without post-traumatic stress disorder.In addition,the heterogeneity of clinical presentations of post-traumatic stress disorder and the overlap of symptoms with other conditions can lead to misdiagnosis and inappropriate treatment.Evidence suggests that this condition is a multisystem disorder that affects many biological systems,raising the possibility that peripheral markers of disease may be used to diagnose post-traumatic stress disorder.We performed a PubMed search for microRNAs(miRNAs)in post-traumatic stress disorder(PTSD)that could serve as diagnostic biomarkers and found 18 original research articles on studies performed with human patients and published January 2012 to December 2023.These included four studies with whole blood,seven with peripheral blood mononuclear cells,four with plasma extracellular vesicles/exosomes,and one with serum exosomes.One of these studies had also used whole plasma.Two studies were excluded as they did not involve microRNA biomarkers.Most of the studies had collected samples from adult male Veterans who had returned from deployment and been exposed to combat,and only two were from recently traumatized adult subjects.In measuring miRNA expression levels,many of the studies had used microarray miRNA analysis,miRNA Seq analysis,or NanoString panels.Only six studies had used real time polymerase chain reaction assay to determine/validate miRNA expression in PTSD subjects compared to controls.The miRNAs that were found/validated in these studies may be considered as potential candidate biomarkers for PTSD and include miR-3130-5p in whole blood;miR-193a-5p,-7113-5p,-125a,-181c,and-671-5p in peripheral blood mononuclear cells;miR-10b-5p,-203a-3p,-4488,-502-3p,-874-3p,-5100,and-7641 in plasma extracellular vesicles/exosomes;and miR-18a-3p and-7-1-5p in blood plasma.Several important limitations identified in the studies need to be taken into account in future studies.Further studies are warranted with war veterans and recently traumatized children,adolescents,and adults having PTSD and use of animal models subjected to various stressors and the effects of suppressing or overexpressing specific microRNAs.

Autism spectrum disorder:difficulties in diagnosis and microRNA biomarkers

We performed a PubMed search for microRNAs in autism spectrum disorder that could serve as diagnostic biomarkers in patients and selected 17 articles published from January 2008 to December 2023,of which 4 studies were performed with whole blood,4 with blood plasma,5 with blood serum,1 with serum neural cell adhesion molecule L1-captured extracellular vesicles,1 with blood cells,and 2 with peripheral blood mononuclear cells.Most of the studies involved children and the study cohorts were largely males.Many of the studies had performed microRNA sequencing or quantitative polymerase chain reaction assays to measure microRNA expression.Only five studies had used real-time polymerase chain reaction assay to validate microRNA expression in autism spectrum disorder subjects compared to controls.The microRNAs that were validated in these studies may be considered as potential candidate biomarkers for autism spectrum disorder and include miR-500a-5p,-197-5p,-424-5p,-664a-3p,-365a-3p,-619-5p,-664a-3p,-3135a,-328-3p,and-500a-5p in blood plasma and miR-151a-3p,-181b-5p,-320a,-328,-433,-489,-572,-663a,-101-3p,-106b-5p,-19b-3p,-195-5p,and-130a-3p in blood serum of children,and miR-15b-5p and-6126 in whole blood of adults.Several important limitations were identified in the studies reviewed,and need to be taken into account in future studies.Further studies are warranted with children and adults having different levels of autism spectrum disorder severity and consideration should be given to using animal models of autism spectrum disorder to investigate the effects of suppressing or overexpressing specific microRNAs as a novel therapy.

Auditory-model-based Feature Extraction Method for Mechanical Faults Diagnosis

It is well known that the human auditory system possesses remarkable capabilities to analyze and identify signals. Therefore, it would be significant to build an auditory model based on the mechanism of human auditory systems, which may improve the effects of mechanical signal analysis and enrich the methods of mechanical faults features extraction. However the existing methods are all based on explicit senses of mathematics or physics, and have some shortages on distinguishing different faults, stability, and suppressing the disturbance noise, etc. For the purpose of improving the performances of the work of feature extraction, an auditory model, early auditory（EA） model, is introduced for the first time. This auditory model transforms time domain signal into auditory spectrum via bandpass filtering, nonlinear compressing, and lateral inhibiting by simulating the principle of the human auditory system. The EA model is developed with the Gammatone filterbank as the basilar membrane. According to the characteristics of vibration signals, a method is proposed for determining the parameter of inner hair cells model of EA model. The performance of EA model is evaluated through experiments on four rotor faults, including misalignment, rotor-to-stator rubbing, oil film whirl, and pedestal looseness. The results show that the auditory spectrum, output of EA model, can effectively distinguish different faults with satisfactory stability and has the ability to suppress the disturbance noise. Then, it is feasible to apply auditory model, as a new method, to the feature extraction for mechanical faults diagnosis with effect.

Stage at diagnosis of colorectal cancer through diagnostic route:Who should be screened?

BACKGROUND Colorectal cancer(CRC)is a global health concern,with advanced-stage diagnoses contributing to poor prognoses.The efficacy of CRC screening has been well-established;nevertheless,a significant proportion of patients remain unscreened,with>70%of cases diagnosed outside screening.Although identifying specific subgroups for whom CRC screening should be particularly recommended is crucial owing to limited resources,the association between the diagnostic routes and identification of these subgroups has been less appreciated.In the Japanese cancer registry,the diagnostic routes for groups discovered outside of screening are primarily categorized into those with comorbidities found during hospital visits and those with CRC-related symptoms.AIM To clarify the stage at CRC diagnosis based on diagnostic routes.METHODS We conducted a retrospective observational study using a cancer registry of patients with CRC between January 2016 and December 2019 at two hospitals.The diagnostic routes were primarily classified into three groups:Cancer screening,follow-up,and symptomatic.The early-stage was defined as Stages 0 or I.Multivariate and univariate logistic regressions were exploited to determine the odds of early-stage diagnosis in the symptomatic and cancer screening groups,referencing the follow-up group.The adjusted covariates were age,sex,and tumor location.RESULTS Of the 2083 patients,715(34.4%),1064(51.1%),and 304(14.6%)belonged to the follow-up,symptomatic,and cancer screening groups,respectively.Among the 2083 patients,CRCs diagnosed at an early stage were 57.3%(410 of 715),23.9%(254 of 1064),and 59.5%(181 of 304)in the follow-up,symptomatic,and cancer screening groups,respectively.The symptomatic group exhibited a lower likelihood of early-stage diagnosis than the follow-up group[P<0.001,adjusted odds ratio(aOR),0.23;95%confidence interval(95%CI):0.19-0.29].The likelihood of diagnosis at an early stage was similar between the follow-up and cancer screening groups(P=0.493,aOR for early-stage diagnosis in the cancer screening group vs follow-up group=1.11;95%CI=0.82-1.49).CONCLUSION CRCs detected during hospital visits for comorbidities were diagnosed earlier,similar to cancer screening.CRC screening should be recommended,particularly for patients without periodical hospital visits for comorbidities.

Value of procalcitonin and presepsin in the diagnosis and severity stratification of sepsis and septic shock

Sepsis is defined as life-threatening organ dysfunction caused by a dysregulated host response to infection.[1,2]Septic shock,the most severe form of sepsis,is characterized by circulatory and cellular/metabolic abnormalities,and can increase mortality to>40%.[1-3]Early recognition and risk stratification of septic shock are crucial but challenging because of the heterogeneity of its presentation and progression.

Marker Ki-67 is a potential biomarker for the diagnosis and prognosis of prostate cancer based on two cohorts

BACKGROUND Prostate cancer(PCa)is a widespread malignancy,predominantly affecting elderly males,and current methods for diagnosis and treatment of this disease continue to fall short.The marker Ki-67(MKI67)has been previously demonstrated to correlate with the proliferation and metastasis of various cancer cells,including those of PCa.Hence,verifying the association between MKI67 and the diagnosis and prognosis of PCa,using bioinformatics databases and clinical data analysis,carries significant clinical implications.AIM To explore the diagnostic and prognostic efficacy of antigens identified by MKI67 expression in PCa.METHODS For cohort 1,the efficacy of MKI67 diagnosis was evaluated using data from The Cancer Genome Atlas(TCGA)and Genotype-Tissue Expression(GTEx)databases.For cohort 2,the diagnostic and prognostic power of MKI67 expression was further validated using data from 271 patients with clinical PCa.RESULTS In cohort 1,MKI67 expression was correlated with prostate-specific antigen(PSA),Gleason Score,T stage,and N stage.The receiver operating characteristic(ROC)curve showed a strong diagnostic ability,and the Kaplan-Meier method demonstrated that MKI67 expression was negatively associated with the progression-free interval(PFI).The time-ROC curve displayed a weak prognostic capability for MKI67 expression in PCa.In cohort 2,MKI67 expression was significantly related to the Gleason Score,T stage,and N stage;however,it was negatively associated with the PFI.The time-ROC curve revealed the stronger prognostic capability of MKI67 in patients with PCa.Multivariate COX regression analysis was performed to select risk factors,including PSA level,N stage,and MKI67 expression.A nomogram was established to predict the 3-year PFI.CONCLUSION MKI67 expression was positively associated with the Gleason Score,T stage,and N stage and showed a strong diagnostic and prognostic ability in PCa.

Dynamic Vision Enabled Contactless Cross-Domain Machine Fault Diagnosis With Neuromorphic Computing

Dear Editor,This letter presents a novel dynamic vision enabled contactless cross-domain fault diagnosis method with neuromorphic computing.The event-based camera is adopted to capture the machine vibration states in the perspective of vision.

Handheld bedside ultrasound in the diagnosis of myocarditis

Myocarditis is a disease process that every emergency physician fears missing.Its severity can be mild to life-threatening,and many cases are likely undetected because they are subclinical with nonspecifi c signs.[1]Subtle cardiac signs may be overshadowed by systemic symptoms of the underlying infectious process.Fever,myalgias,lethargy,symptoms commonly associated with viral syndrome,can mask the life-threatening myocarditis that may be present.In fact,in the United States Myocarditis Treatment Trial,almost 90%of patients reported symptoms consistent with a viral prodrome.[2]Ammirati et al[3]reported that 27%of patients with myocarditis had either reduced left ventricular ejection fraction,ventricular arrhythmias,or low cardiac output.Here,we present a case report,in which handheld point-of-care ultrasound was utilized at the bedside to aid in the critical diagnosis of myocarditis.With the additional information provided through this imaging modality,this patient was able to be transferred to the appropriate tertiary care facility in an expeditious manner and receive possible defi nitive treatment.

Chinese Guidelines for the Diagnosis and Management of Atrial Fibrillation

Atrial fibrillation(AF)is the most common sustained cardiac arrhythmia,significantly impacting patients’quality of life and increasing the risk of death,stroke,heart failure,and dementia.Over the past two decades,there have been significant breakthroughs in AF risk prediction and screening,stroke prevention,rhythm control,catheter ablation,and integrated management.During this period,the scale,quality,and experience of AF management in China have greatly improved,providing a solid foundation for the development of guidelines for the diagnosis and management of AF.To further promote standardized AF management,and apply new technologies and concepts to clinical practice in a timely and comprehensive manner,the Chinese Society of Cardiology of the Chinese Medical Association and the Heart Rhythm Committee of the Chinese Society of Biomedical Engineering have jointly developed the Chinese Guidelines for the Diagnosis and Management of Atrial Fibrillation.The guidelines have comprehensively elaborated on various aspects of AF management and proposed the CHA2DS2-VASc-60 stroke risk score based on the characteristics of AF in the Asian population.The guidelines have also reevaluated the clinical application of AF screening,emphasized the significance of early rhythm control,and highlighted the central role of catheter ablation in rhythm control.

Circular RNAs in breast cancer diagnosis,treatment and prognosis

Breast cancer has surpassed lung cancer to become the most common malignancy worldwide.The incidence rate and mortality rate of breast cancer continue to rise,which leads to a great burden on public health.Circular RNAs(circRNAs),a new class of noncoding RNAs(ncRNAs),have been recognized as important oncogenes or suppressors in regulating cancer initiation and progression.In breast cancer,circRNAs have significant roles in tumorigenesis,recurrence and multidrug resistance that are mediated by various mechanisms.Therefore,circRNAs may serve as promising targets of therapeutic strategies for breast cancer management.This study reviews the most recent studies about the biosynthesis and characteristics of circRNAs in diagnosis,treatment and prognosis evaluation,as well as the value of circRNAs in clinical applications as biomarkers or therapeutic targets in breast cancer.Understanding the mechanisms by which circRNAs function could help transform basic research into clinical applications and facilitate the development of novel circRNA-based therapeutic strategies for breast cancer treatment.

Laser spectroscopy imaging technique coupled withnanomaterials for cancer diagnosis: A review

Laser spectroscopic imaging techniques have received tremendous attention in the-eld of cancer diagnosis due to their high sensitivity,high temporal resolution,and short acquisition time.However,the limited tissue penetration of the laser is still a challenge for the in vivo diagnosis of deep-seated lesions.Nanomaterials have been universally integrated with spectroscopic imaging techniques for deeper cancer diagnosis in vivo.The components,morphology,and sizes of nanomaterials are delicately designed,which could realize cancer diagnosis in vivo or in situ.Considering the enhanced signal emitting from the nanomaterials,we emphasized their combination with spectroscopic imaging techniques for cancer diagnosis,like the surface-enhanced Raman scattering(SERS),photoacoustic,fluorescence,and laser-induced breakdown spectroscopy(LIBS).Applications ofthe above spectroscopic techniques offer new prospectsfor cancer diagnosis.

Diagnosis of poorly differentiated adenocarcinoma of the stomach by confocal laser endomicroscopy:A case report

BACKGROUND In recent years,confocal laser endomicroscopy(CLE)has become a new endoscopic imaging technology at the microscopic level,which is extensively performed for real-time in vivo histological examination.CLE can be performed to distinguish benign from malignant lesions.In this study,we diagnosed using CLE an asymptomatic patient with poorly differentiated gastric adenocarcinoma.CASE SUMMARY A 63-year-old woman was diagnosed with gastric mucosal lesions,which may be gastric cancer,in the small curvature of the stomach by gastroscopy.She consented to undergo CLE for morphological observation of the gastric mucosa.Through the combination of CLE diagnosis and postoperative pathology,the intraoperative CLE diagnosis was considered to be reliable.According to our experience,CLE can be performed as the first choice for the diagnosis of gastric cancer.CONCLUSION CLE has several advantages over pathological diagnosis.We believe that CLE has great potential in the diagnosis of benign and malignant gastric lesions.

Exploring impedance spectrum for lithium-ion batteries diagnosis and prognosis:A comprehensive review

Lithium-ion batteries have extensive usage in various energy storage needs,owing to their notable benefits of high energy density and long lifespan.The monitoring of battery states and failure identification are indispensable for guaranteeing the secure and optimal functionality of the batteries.The impedance spectrum has garnered growing interest due to its ability to provide a valuable understanding of material characteristics and electrochemical processes.To inspire further progress in the investigation and application of the battery impedance spectrum,this paper provides a comprehensive review of the determination and utilization of the impedance spectrum.The sources of impedance inaccuracies are systematically analyzed in terms of frequency response characteristics.The applicability of utilizing diverse impedance features for the diagnosis and prognosis of batteries is further elaborated.Finally,challenges and prospects for future research are discussed.

Application of artificial intelligence in the diagnosis and treatment of Kawasaki disease

This editorial provides commentary on an article titled"Potential and limitationsof ChatGPT and generative artificial intelligence(AI)in medical safety education"recently published in the World Journal of Clinical Cases.AI has enormous potentialfor various applications in the field of Kawasaki disease(KD).One is machinelearning(ML)to assist in the diagnosis of KD,and clinical prediction models havebeen constructed worldwide using ML;the second is using a gene signalcalculation toolbox to identify KD,which can be used to monitor key clinicalfeatures and laboratory parameters of disease severity;and the third is using deeplearning(DL)to assist in cardiac ultrasound detection.The performance of the DLalgorithm is similar to that of experienced cardiac experts in detecting coronaryartery lesions to promoting the diagnosis of KD.To effectively utilize AI in thediagnosis and treatment process of KD,it is crucial to improve the accuracy of AIdecision-making using more medical data,while addressing issues related topatient personal information protection and AI decision-making responsibility.AIprogress is expected to provide patients with accurate and effective medicalservices that will positively impact the diagnosis and treatment of KD in thefuture.

Expert Experience and Data-Driven Based Hybrid Fault Diagnosis for High-SpeedWire Rod Finishing Mills

The reliable operation of high-speed wire rod finishing mills is crucial in the steel production enterprise.As complex system-level equipment,it is difficult for high-speed wire rod finishing mills to realize fault location and real-time monitoring.To solve the above problems,an expert experience and data-driven-based hybrid fault diagnosis method for high-speed wire rod finishing mills is proposed in this paper.First,based on its mechanical structure,time and frequency domain analysis are improved in fault feature extraction.The approach of combining virtual value,peak value with kurtosis value index,is adopted in time domain analysis.Speed adjustment and side frequency analysis are proposed in frequency domain analysis to obtain accurate component characteristic frequency and its corresponding sideband.Then,according to time and frequency domain characteristics,fault location based on expert experience is proposed to get an accurate fault result.Finally,the proposed method is implemented in the equipment intelligent diagnosis system.By taking an equipment fault on site,for example,the effectiveness of the proposed method is illustrated in the system.