Prevention of medical errors

Development, Validation, and Comparison of Machine Learning Models for Predicting Pediatric Surgical Site Infections Using the NSQIP-P Database.

BACKGROUND: Surgical site infections (SSIs) cause substantial postoperative morbidity in children. Despite being largely preventable, SSI rates have continued to rise. Existing SSI predictive models are predominantly designed for adults. This study aimed to develop, validate, and compare machine learning models for predicting pediatric SSI risk and recommend a model for clinical workflow integrati...

Overview of a User-Centered, Mixed-Methods Process for Designing Interconnected and Focused Mobile Applications on Patient Care Environment (InterFACE): Augmented-Reality Decision Support System for Pediatric Resuscitation.

BACKGROUND: Pediatric cardiopulmonary resuscitation (CPR) is a highly complex and time-critical process that demands precise team coordination and strict adherence to pediatric advanced life support (PALS) guidelines. In real-world practice, adherence often deteriorates due to cognitive overload, fragmented communication, and disruption of information flow under stress. Although digital cognitive ...

Can Artificial Intelligence Align with Evidence? Performance of ChatGPT-4o in Knee Osteoarthritis Surgical Guidelines.

Artificial intelligence large language models (LLMs) such as ChatGPT are increasingly used in clinical settings, yet their reliability in reproducing ...

Predictive artificial intelligence in maxillofacial surgery: a systematic review.

The objective of this systematic review is to outline the current landscape and applications of predictive artificial intelligence (AI) in maxillofaci...

Enhancing dental clinical education through AI: insights into post-clinical summaries.

BACKGROUND: Artificial Intelligence (AI) is increasingly being introduced into clinical education, including dentistry, as a supplement to traditional...

[Sudden cardiac death in structural heart disease : Update on prevention].

Sudden cardiac death (SCD) remains one of the leading causes of death despite major advances in cardiovascular diagnostics and treatment. Evidence sup...

A new adaptive federated learning approach for privacy preserving UAV anomaly detection under non-IID distributions.

Robust and personalized anomaly detection is essential due to the rapid growth of UAV deployments in critical infrastructure, logistics, and surveilla...

Expert Consensus on Ethical Governance for Clinical Applications of Generative Medical Artificial Intelligence(2025 Edition).

The research and innovative applications of generative medical artificial intelligence(GMAI)are rapidly advancing in the healthcare field.Significant ...

Criteria to Assess the Predictive and Clinical Utility of Novel Models, Biomarkers, and Tools for Risk of Cardiovascular Disease: A Scientific Statement From the American Heart Association.

Risk prediction has been used in the primary prevention of cardiovascular disease for >3 decades. Contemporary cardiovascular risk assessment relies o...

AI-driven diagnosis of acute aortic syndrome based on multi-modal information fusion.

Acute aortic syndrome (AAS) is a severe cardiovascular disorder with a high mortality rate in the early stage of onset. In this study, the aim was to ...

[Pay attention to blepharospasm and dry eye].

Blepharospasm-related dry eye is a complex multifactorial comorbidity involving neural, ocular surface, and psychological factors, currently facing co...

Multi-model large-scale AI framework for avian influenza surveillance and preparedness: Harnessing large language models to enhance risk communication, real-time decision support, and public health response strategies.

Avian influenza remains a persistent threat to global health security, with serious consequences for food systems, trade, and pandemic preparedness. T...

Medical intelligence vs. artificial intelligence - How psychiatrists arrive at treatment algorithms.

The rise of artificial intelligence and computational methods in clinical decision-making allows for a novel perspective on personalized psychopharmac...

Artificial intelligence virtual extracellular vesicles (AIVEVs).

Recent progress in artificial intelligence (AI) has given rise to AI virtual cells (AIVCs), which are digital twins of predictable or dynamic biologic...

Leveraging AI for Analysis of Digital Health Information on Cancer Prevention Among Arab Youth and Adults: Content Analysis.

BACKGROUND: As TikTok (ByteDance) grows as a major platform for health information, the quality and accuracy of Arabic-language cancer prevention cont...

Ninja optimization algorithm based ultra wideband antenna electromagnetic band gap modeling via a generative adversarial network.

Ultra-wideband antennas with electromagnetic band-gap (EBG) structures play a crucial role in next-generation wireless and energy-efficient communicat...

The longitudinal relationships between Internet adaptability and usage behavior on AI-driven healthcare platforms: A cross-lagged panel network analysis.

Internet adaptability on artificial intelligence (AI) healthcare platforms is a key factor influencing users' continued usage and the effectiveness of...

Existing and future use cases, and safety and ethical considerations for AI in body image, and eating disorder prevention.

Artificial intelligence (AI) is rapidly transforming digital, clinical, and cultural landscapes in ways that hold significant implications for body im...

Predicting recurrent cardiac arrest within one year after surviving In-Hospital Cardiac Arrest using a machine learning model.

BACKGROUND: Patients discharged alive after in-hospital cardiac arrest (IHCA) have an increased mortality up to a year after hospital discharge. Impro...

Ambient AI Documentation and Patient Satisfaction in Outpatient Care: Retrospective Pilot Study.

BACKGROUND: Patient experience is a critical consideration for any health care institution. Leveraging artificial intelligence (AI) to improve health ...