BACKGROUND: Large language models (LLMs) are revolutionizing natural language processing, increasingly applied in clinical settings to enhance preoperative patient education.
OBJECTIVES: Training public health personnel is crucial for enhancing the capacity of public health systems. However, existing research often falls short in providing a comprehensive theoretical framework and fails to account for the intricate interp...
BACKGROUND: Over 96% of adult women face health issues, with 70% experiencing conditions like infections. Mobile health education is increasingly popular but faces challenges in personalization and readability. Artificial intelligence (AI) chatbots p...
Journal of health organization and management
Jun 5, 2025
PURPOSE: Digital health or digital healthcare, is a broad, multidisciplinary concept that includes concepts from an intersection between technology and healthcare. Digital health applies digital transformation to the healthcare field, incorporating s...
Mental health disorders like depression, anxiety, and stress (DAS) are rising globally. Understanding how diet and lifestyle influence these conditions is vital for targeted interventions. This study explores the potential of machine learning (ML) to...
Colorectal disease : the official journal of the Association of Coloproctology of Great Britain and Ireland
Jun 1, 2025
AIM: Well-leg compartment syndrome (WLCS) is a serious complication of prolonged surgery in the head-down tilt lithotomy (HDTL) position associated with increased postoperative morbidity and mortality. However, there is a lack of awareness and clinic...
IMPORTANCE: Sepsis is a major cause of morbidity and mortality, with early intervention shown to improve outcomes. Predictive modeling and artificial intelligence (AI) can aid in early sepsis recognition, but there remains a gap between algorithm dev...
OBJECTIVE: To assess the knowledge, attitudes, and practices (KAP) of medical stakeholders regarding the use of generative artificial intelligence (GAI) tools.
Negative academic emotions reflect the negative experiences that learners encounter during the learning process. This study aims to explore the effectiveness of machine learning algorithms in predicting high school students' negative academic emotion...
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