AI Medical Compendium Journal:
Journal of medical Internet research

Showing 1 to 10 of 745 articles

A Deep Learning Model for Identifying the Risk of Mesenteric Malperfusion in Acute Aortic Dissection Using Initial Diagnostic Data: Algorithm Development and Validation.

Journal of medical Internet research
BACKGROUND: Mesenteric malperfusion (MMP) is an uncommon but devastating complication of acute aortic dissection (AAD) that combines 2 life-threatening conditions-aortic dissection and acute mesenteric ischemia. The complex pathophysiology of MMP pos...

Women's Preferences and Willingness to Pay for AI Chatbots in Women's Health: Discrete Choice Experiment Study.

Journal of medical Internet research
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...

Improving Patient Communication by Simplifying AI-Generated Dental Radiology Reports With ChatGPT: Comparative Study.

Journal of medical Internet research
BACKGROUND: Medical reports, particularly radiology findings, are often written for professional communication, making them difficult for patients to understand. This communication barrier can reduce patient engagement and lead to misinterpretation. ...

Clinical Management of Wasp Stings Using Large Language Models: Cross-Sectional Evaluation Study.

Journal of medical Internet research
BACKGROUND: Wasp stings are a significant public health concern in many parts of the world, particularly in tropical and subtropical regions. The venom of wasps contains a variety of bioactive compounds that can lead to a wide range of clinical effec...

A Comprehensive Drift-Adaptive Framework for Sustaining Model Performance in COVID-19 Detection From Dynamic Cough Audio Data: Model Development and Validation.

Journal of medical Internet research
BACKGROUND: The COVID-19 pandemic has highlighted the need for robust and adaptable diagnostic tools capable of detecting the disease from diverse and continuously evolving data sources. Machine learning models, particularly convolutional neural netw...

Enhancing the Accuracy of Human Phenotype Ontology Identification: Comparative Evaluation of Multimodal Large Language Models.

Journal of medical Internet research
BACKGROUND: Identifying Human Phenotype Ontology (HPO) terms is crucial for diagnosing and managing rare diseases. However, clinicians, especially junior physicians, often face challenges due to the complexity of describing patient phenotypes accurat...

Trust, Trustworthiness, and the Future of Medical AI: Outcomes of an Interdisciplinary Expert Workshop.

Journal of medical Internet research
Trustworthiness has become a key concept for the ethical development and application of artificial intelligence (AI) in medicine. Various guidelines have formulated key principles, such as fairness, robustness, and explainability, as essential compon...

Evaluating User Interactions and Adoption Patterns of Generative AI in Health Care Occupations Using Claude: Cross-Sectional Study.

Journal of medical Internet research
BACKGROUND: Generative artificial intelligence (GenAI) systems like Anthropic's Claude and OpenAI's ChatGPT are rapidly being adopted in various sectors, including health care, offering potential benefits for clinical support, administrative efficien...

Attitudes Toward AI Usage in Patient Health Care: Evidence From a Population Survey Vignette Experiment.

Journal of medical Internet research
BACKGROUND: The integration of artificial intelligence (AI) holds substantial potential to alter diagnostics and treatment in health care settings. However, public attitudes toward AI, including trust and risk perception, are key to its ethical and e...

Predictive Models Using Machine Learning to Identify Fetal Growth Restriction in Patients With Preeclampsia: Development and Evaluation Study.

Journal of medical Internet research
BACKGROUND: Fetal growth restriction (FGR) is a common complication of preeclampsia. FGR in patients with preeclampsia increases the risk of neonatal-perinatal mortality and morbidity. However, previous prediction methods for FGR are class-biased or ...