Patient safety / Risk Management

Artificial intelligence for real-time motion tracking in MRI-guided radiotherapy: A systematic review.

BACKGROUND AND PURPOSE: Intrafraction motion compromises accurate dose delivery in MRI-guided radiotherapy (MRIgRT), motivating the adoption of artificial intelligence (AI). This systematic review aims to evaluate the performance of AI-driven motion tracking approaches and identify barriers to clinical translation. METHODS: PubMed and Web of Science were searched from January 1, 2020, to January 1...

Reproducibility, validation, and failure modes across classical and AI-driven molecular docking.

Molecular docking is indispensable across computer‑aided discovery. However, its conclusions often hinge more on modeling choices than on software brand or nominal score. In this review, we argue that docking should be treated explicitly as conditional modeling whose interpretability depends on structural provenance, ligand‑state definition, search‑space design, and validation under deployment‑rel...

AI Chatbot Use and Disclosure for Mental Health Among US Adolescents and Young Adults.

IMPORTANCE: The rapid expansion of artificial intelligence (AI) chatbots has coincided with a persistent youth mental health crisis in the US, raising...

Beyond Training: Systems Framework for Sustainable Health Informatics Investment in Africa.

Across Africa, substantial investment has built national health information systems (HISs), including the surveillance platforms, reporting tools, and...

Digital Health in Midwifery Practice: A Qualitative Review of Midwives' Experiences and Perceptions.

AIM: To synthesize qualitative evidence on midwives' experiences and perceptions regarding the use of digital health technologies in clinical maternit...

Ambiguity of Disclosure Criteria of Artificial Intelligence Use in Medical Writing.

Machine learning prediction of PICC-associated thrombotic complications in critically ill patients.

BACKGROUND: Peripherally inserted central catheters (PICCs) are widely used vascular access devices in intensive care, yet thrombotic complications re...

Clinical governance of artificial intelligence in internal medicine: a literature-informed five-pillar framework for complex care.

Most artificial intelligence (AI) governance frameworks in healthcare address model development, reporting standards, or regulation in broad terms, bu...

Deep Learning-Based Quantification of Vitreous Hyperreflective Foci as a Biomarker for Intraocular Inflammation.

OBJECTIVE: To develop and validate an artificial intelligence (AI)-driven pipeline to quantify vitreous hyperreflective foci (vHRF) from OCT images an...

Physics-informed machine learning for cross-study prediction of oil-water membrane fouling.

Performance decay driven by coupled transport, accumulation, and removal processes remains a central challenge in many chemical engineering systems. M...

Rapid Access Macular Screening and Evaluation: A Datasheet for a Dataset to Diagnose and Triage Macular Diseases.

PURPOSE: Macular disease can cause significant visual morbidity. Timely and accurate diagnosis and management is paramount. However, there is a lack o...

Detection of Microbehavior Intervals for Predicting Mental Health: Clinically Relevant and Advanced Multimodal Temporal Analysis.

BACKGROUND: Health care workers (HCWs) face sustained psychological demands that place them at heightened risk for burnout and posttraumatic stress di...

Image-Quality-Aware Multimodal Artificial Intelligence for Automated Structured OCT Report Generation in Glaucoma Evaluation.

OBJECTIVE: To develop an explainable multimodal large language model (MM-LLM) that (1) screens optic nerve head (ONH) OCT circle scans for quality and...

Artificial intelligence policy among nursing journals.

BACKGROUND: The rapid integration of generative artificial intelligence (AI) into scholarly work is reshaping nursing publication standards. PURPOSE: ...

Artificial intelligence in drug discovery for fungal diseases: a scoping review.

BACKGROUND: Fungal diseases represent a global health threat, with high mortality rates and growing antifungal resistance demanding new therapeutic st...

Fusing Structural Phenotypes with Functional Data for Early Prediction of Primary Angle-Closure Glaucoma Progression.

PURPOSE: To classify eyes as slow or fast glaucoma progressors in patients with primary angle-closure glaucoma (PACG) using an integrated approach com...

A Disorder-Aware Computational Framework to Identify Structurally Tractable Targets in Proliferative Vitreoretinopathy.

OBJECTIVE: Proliferative vitreoretinopathy (PVR) remains a major cause of failure after rhegmatogenous retinal detachment repair and lacks effective p...

Ethics and Fairness Considerations in AI-Based Deception Detection Technologies for Mental Health Applications: Focus Group Study.

BACKGROUND: Artificial intelligence (AI) technologies are increasingly being integrated into mental health settings to support tasks such as clinical ...

Patients' Perspectives on the Implementation of AI in Radiological Diagnostics: Focus Group Study.

BACKGROUND: Rapid developments in artificial intelligence (AI) will enable its widespread use in radiological diagnostics in the near future. Patients...

Deep Learning and Radiomics Assessment for Highly Myopic Glaucoma Detection Based on Fundus Photography.

PURPOSE: To investigate spatially distinctive features in fundus photographs of highly myopic glaucoma (HMG) by integrating radiomics and deep learnin...