AI Medical Compendium Topic

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Performance of ChatGPT-4 on Taiwanese Traditional Chinese Medicine Licensing Examinations: Cross-Sectional Study.

JMIR medical education
BACKGROUND: The integration of artificial intelligence (AI), notably ChatGPT, into medical education, has shown promising results in various medical fields. Nevertheless, its efficacy in traditional Chinese medicine (TCM) examinations remains underst...

Chat GPT, Gemini or Meta AI: A comparison of AI platforms as a tool for answering higher-order questions in microbiology.

Journal of postgraduate medicine
INTRODUCTION: Artificial intelligence (AI) platforms have achieved a noteworthy role in various fields of medical sciences, ranging from medical education to clinical diagnostics and treatment. ChatGPT, Gemini, and Meta AI are some large language mod...

Machine learning for predicting metabolic-associated fatty liver disease including NHHR: a cross-sectional NHANES study.

PloS one
OBJECTIVE: Metabolic - associated fatty liver disease (MAFLD) is a common hepatic disorder with increasing prevalence, and early detection remains inadequately achieved. This study aims to explore the relationship between the non-high-density lipopro...

Presenting a prediction model for HELLP syndrome through data mining.

BMC medical informatics and decision making
BACKGROUND: The HELLP syndrome represents three complications: hemolysis, elevated liver enzymes, and low platelet count. Since the causes and pathogenesis of HELLP syndrome are not yet fully known and well understood, distinguishing it from other pr...

Development of an explainable machine learning model for predicting depression in adolescent girls with non-suicidal self-injury: A cross-sectional multicenter study.

Journal of affective disorders
Non-suicidal self-injury (NSSI) in adolescent girls is a critical predictor of subsequent depression and suicide risk, yet current tools lack both accuracy and clinical interpretability. We developed the first explainable machine learning model integ...

Awareness of the Role of Artificial Intelligence in Health Care among Undergraduate Nursing Students: A Descriptive Cross-Ssectional Study.

Nurse education today
BACKGROUND: Artificial intelligence (AI) has the potential to revolutionize healthcare by improving efficiency and reducing errors; however, challenges such as inadequate funding and lack of awareness among healthcare professionals hinder its integra...

Retinal vein occlusion risk prediction without fundus examination using a no-code machine learning tool for tabular data: a nationwide cross-sectional study from South Korea.

BMC medical informatics and decision making
BACKGROUND: Retinal vein occlusion (RVO) is a leading cause of vision loss globally. Routine health check-up data-including demographic information, medical history, and laboratory test results-are commonly utilized in clinical settings for disease r...

A machine learning approach to predict treatment efficacy and adverse effects in major depression using CYP2C19 and clinical-environmental predictors.

Psychiatric genetics
BACKGROUND: Major depressive disorder (MDD) is among the leading causes of disability worldwide and treatment efficacy is variable across patients. Polymorphisms in cytochrome P450 2C19 (CYP2C19) play a role in response and side effects to medication...