AI Medical Compendium

Use of Commercially Available Large Language Models to Generate Information Leaflets on Post-Intensive Care Syndrome: Clinical Utility Assessment.

JMIR formative research May 14, 2026

BACKGROUND: Patients and their families without medical knowledge may find professional health care information difficult to understand. The use of large language models (LLMs) to simplify and translate complex medical content holds promise for impro... read more

Multilevel Determinants of Engagement in Lifelong Learning in Orthodontics From Formal to AI-Supported Approaches: Development of a Conceptual Framework Through a Qualitative Study.

JMIR medical education May 14, 2026

BACKGROUND: Lifelong learning (LLL) is increasingly important for health care professionals, particularly within the field of orthodontics, driven by emerging technologies, updated treatment techniques, and rising patient expectations. To maintain co... read more

Multimodal Fusion of Echocardiogram Images and Electronic Medical Records for Heart Disease Screening: Retrospective Algorithm Development and Validation Study.

JMIR medical informatics May 14, 2026

BACKGROUND: Echocardiography is a fundamental imaging modality for the diagnosis of heart disease (HD), but its interpretation remains operator-dependent and lacks standardized, data-driven decision support. Although artificial intelligence has impro... read more

QUASAR: A Universal Autonomous System for Atomistic Simulation and a Benchmark of Its Capabilities.

Journal of chemical information and modeling May 14, 2026

The integration of large language models (LLMs) into materials science offers a transformative opportunity to streamline computational workflows, yet current agentic systems remain constrained by rigid, carefully crafted domain-specific tool-calling ... read more

Hematopoietic Stem Cell Transplant and Brain Volume Changes in Adults With Sickle Cell Disease.

Neurology May 14, 2026

BACKGROUND AND OBJECTIVES: Adults with sickle cell disease (SCD) are at risk of decline in brain health and cognition, even without clinical stroke. SCD-related changes on MRI include brain atrophy and T2 fluid attenuated inversion recovery (FLAIR) w... read more

Machine Learning and Deep Learning Models for Predicting Future Falls in Community-Dwelling Older Adults: Systematic Review and Meta-Analysis of Longitudinal Evidence.

Journal of medical Internet research May 14, 2026

BACKGROUND: Machine learning (ML) and deep learning (DL) show promise for fall risk prediction, but prior reviews focused mainly on real-time fall detection, in-hospital falls, or conventional statistical models. The performance of ML-DL-based models... read more

A Natural Language Processing Framework for Structuring and Visualizing Clinical Trial Eligibility Criteria at Scale: Protocol for a Quantitative Study.

JMIR research protocols May 14, 2026

BACKGROUND: Eligibility criteria are essential to clinical trial design, guiding recruitment, and ensuring patient safety and scientific rigor. However, criteria are often lengthy, heterogeneous, and inconsistently formatted, which hinders large-scal... read more

HIV and Substance Use Reduction for Youth Experiencing Homelessness: Development and Usability Study.

JMIR formative research May 14, 2026

BACKGROUND: Youth experiencing homelessness face heightened vulnerability to HIV infection and substance use due to complex structural, psychosocial, and behavioral factors. Despite increased mobile phone access among youth experiencing homelessness,... read more

Cross-Dataset Evaluation of an Automated Video-Based Model for Detecting Tardive Dyskinesia Using the Clinician's Tardive Inventory: Validation Study.

JMIR mental health May 14, 2026

BACKGROUND: Tardive dyskinesia (TD) is a common, often underrecognized movement disorder resulting from long-term antipsychotic use, yet its detection in routine mental health care remains inconsistent despite the availability of structured rating sc... read more

Evaluating Encoder and Decoder Models for Extended Clinical Concept Recognition in Japanese Clinical Texts: Comparative Study With Weighted Soft Matching.