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Peer Relationships Are a Direct Cause of the Adolescent Mental Health Crisis: Interpretable Machine Learning Analysis of 2 Large Cohort Studies.

JMIR public health and surveillance
BACKGROUND: Converging evidence indicates an adolescent mental health crisis in Western societies that has developed and exacerbated over the past decade. The proposed driving factors of this trend include more screen time, physical inactivity, and s...

Machine Learning Model for Predicting Coronary Heart Disease Risk: Development and Validation Using Insights From a Japanese Population-Based Study.

JMIR cardio
BACKGROUND: Coronary heart disease (CHD) is a major cause of morbidity and mortality worldwide. Identifying key risk factors is essential for effective risk assessment and prevention. A data-driven approach using machine learning (ML) offers advanced...

Stigma Attitudes Toward HIV/AIDS From 2011 Through 2023 in Japan: Retrospective Study in Japan.

Journal of medical Internet research
BACKGROUND: Stigma associated with HIV/AIDS continues to be a major barrier to prevention, management, and care. HIV stigma can negatively influence health behaviors. Surveys of the general public in Japan also demonstrated substantial gaps in knowle...

Global Health care Professionals' Perceptions of Large Language Model Use In Practice: Cross-Sectional Survey Study.

JMIR medical education
BACKGROUND: ChatGPT is a large language model-based chatbot developed by OpenAI. ChatGPT has many potential applications to health care, including enhanced diagnostic accuracy and efficiency, improved treatment planning, and better patient outcomes. ...

Classifying the Information Needs of Survivors of Domestic Violence in Online Health Communities Using Large Language Models: Prediction Model Development and Evaluation Study.

Journal of medical Internet research
BACKGROUND: Domestic violence (DV) is a significant public health concern affecting the physical and mental well-being of numerous women, imposing a substantial health care burden. However, women facing DV often encounter barriers to seeking in-perso...

Impact of a "Digital Health" Curriculum on Students' Perception About Competence and Relevance of Digital Health Topics for Future Professional Challenges: Prospective Pilot Study.

JMIR formative research
BACKGROUND: The rapid integration of digital technologies in health care has emphasized the need to ensure that medical students are well-equipped with the knowledge and competencies related to digital health.

Decoding Digital Discourse Through Multimodal Text and Image Machine Learning Models to Classify Sentiment and Detect Hate Speech in Race- and Lesbian, Gay, Bisexual, Transgender, Queer, Intersex, and Asexual Community-Related Posts on Social Media: Quantitative Study.

Journal of medical Internet research
BACKGROUND: A major challenge in sentiment analysis on social media is the increasing prevalence of image-based content, which integrates text and visuals to convey nuanced messages. Traditional text-based approaches have been widely used to assess p...

Evaluation and Bias Analysis of Large Language Models in Generating Synthetic Electronic Health Records: Comparative Study.

Journal of medical Internet research
BACKGROUND: Synthetic electronic health records (EHRs) generated by large language models (LLMs) offer potential for clinical education and model training while addressing privacy concerns. However, performance variations and demographic biases in th...

A novel predictive method for URS and laser lithotripsy using machine learning and explainable AI: results from the FLEXOR international database.

World journal of urology
PURPOSE: We developed Machine learning (ML) algorithms to predict ureteroscopy (URS) outcomes, offering insights into diagnosis and treatment planning, personalised care and improved clinical decision-making.

A machine learning-based prediction model for colorectal liver metastasis.

Clinical and experimental medicine
Colorectal liver metastasis (CRLM) is a primary factor contributing to poor prognosis and metastasis in colorectal cancer (CRC) patients. This study aims to develop and validate a machine learning (ML)-based risk prediction model using conventional c...