Prevention of medical errors

Artificial intelligence in the management of sports knee injuries: a narrative review.

INTRODUCTION: Sports-related knee injuries are common and debilitating, often leading to chronic pain, early osteoarthritis, and reduced performance. Artificial Intelligence (AI) has emerged as a promising tool to improve their prevention, diagnosis, prognosis, and rehabilitation. This review summarises current evidence on the clinical applications, limitations, and future directions of AI and mac...

Baseline symptom severity and response to multisession cathodal transcranial direct current stimulation in adolescents and young adults with autism: an exploratory analysis.

BACKGROUND: Identifying baseline clinical characteristics associated with treatment response is crucial for optimising intervention strategies in people with autism spectrum disorder (ASD). This study aimed to distinguish responders from non-responders to a multisession prefrontal transcranial direct current stimulation (tDCS) protocol and to explore how baseline individual characteristics relate ...

Comparing AI-Assisted Coding and Traditional Qualitative Analysis: a Study Examining Differences in Methods and Results of AI-Assisted Coding and Traditional Content Coding Using Community Engagement Data Collected During the Development of a Municipal Food Plan.

Qualitative data poses a challenge for prevention science and public health, as it is critical to explain the context of communities, health, and beha...

Opposition to Youth e-Cigarette Prevention Campaigns on Twitter and TikTok: Cross-Platform Observational Mixed Methods Analysis.

BACKGROUND: Youth e-cigarette use rose sharply between 2013 and 2024 in the United States, prompting widespread prevention campaigns at national, stat...

AI-generated Feedback Following Social Robotic Virtual Patient Interactions and Medical Student Performance: Nonrandomized Quasi-Experimental Study.

BACKGROUND: Virtual patients (VPs) demonstrate effectiveness in improving clinical reasoning skills; however, traditional VP platforms often lack indi...

Multi-output LSTM-based prediction of postoperative delirium: integrating baseline and perioperative data for enhanced risk stratification in older spine surgery patients.

INTRODUCTION: Postoperative delirium (POD) adversely affects clinical outcomes among older adults undergoing spine surgery. However, existing predicti...

Validity evidence for the communication learning assessment: Prior coursework as a known group.

BACKGROUND: Effective physician-patient communication is a core component of high-quality medical care, yet it remains challenging to teach and assess...

Digital pathology platforms with integrated AI algorithms: a structured landscape analysis and recommendations for clinical implementation.

Pathology is undergoing a fundamental change as slide-based diagnostics transition toward digital workflows. Advances in whole slide imaging, data man...

Communication, compassion, and shared decision-making in allergy.

Shared decision-making (SDM) is a structured approach to clinical care that integrates the best available evidence, clinician expertise, and patient v...

Predicting the Timing of the Metabolic Inflection Point in Type 1 Diabetes Progression Using Machine Learning and Survival Analysis Models.

We undertook this study to improve early identification of the metabolic inflection point (IP) preceding clinical type 1 diabetes in autoantibody-posi...

Challenges and Opportunities for Improved Tuberculosis and HIV Prevention in South America.

Tuberculosis (TB) and human immunodeficiency virus (HIV) cause significant morbidity and mortality in South America. Despite the advances in active ca...

Evaluating real-time voice AI-based virtual patients for authentic communication training.

BACKGROUND: Effective communication is essential in clinical training, yet opportunities for realistic and interactionally authentic practice remain l...

Creativity as a core competency in medical education: the art of medicine.

As medical education increasingly prioritises standardisation and algorithmic decision-making, the qualities that define the 'art' of medicine-improvi...

Disseminating Health Prevention Programs Using AI-Crafted, Culturally Tailored Ads for Somali American Adolescents.

Recent advancements in artificial intelligence (AI) and digital health messaging present opportunities to bridge service health gaps in underserved co...

Large Language Models for Cochlear Implant Education: A Comparison of ChatGPT, Gemini, Claude, and DeepSeek.

OBJECTIVE: Artificial intelligence-supported large language models (LLMs) have become increasingly widespread in recent years in the health communicat...

Modernizing public health surveillance for global health security leveraging AI.

An electronic public health surveillance (e-PHS) embracing One Health and participatory approaches will collect and analyze data at the human-animal-e...

Blockchain-driven trust management and AI computing for sensor networks optimization.

The Internet of Things (IoT) and emerging technologies have converged to drive the remarkable development of intelligent systems. The interconnection ...

Machine learning-based prediction of BV-relevant probiotic functional potential in vaginal-derived Lactobacillus crispatus strains.

The vaginal microbiota plays a pivotal role in maintaining female reproductive health and homeostasis. However, most currently available Lactobacillus...

'Bad manners'-refocusing on 'bedside manner' as a core professional behaviour for doctors.

Healthcare systems globally face unprecedented pressures, with increasing patient volumes and resource constraints affecting care delivery. While syst...

Advancing Nursing Data Integration Through a Nursing Minimum Dataset for the Conceptual and Technical Development of a "Fall Prevention" Data Module: Development Study.

BACKGROUND: In aging populations, the demand for care, including care delivery in long-term care (LTC) facilities, is increasing. This situation highl...