Prevention of medical errors

Ethical Use of Artificial Intelligence in Public Health: Mitigating Risks and Advancing Health Equity.

Artificial intelligence (AI) is increasingly integrated into public health practice, offering new tools for surveillance, behavioral interventions, disease prevention, risk communication, and population health management. Although AI demonstrates promise for earlier disease detection, improved intervention targeting, and cost-effective augmentation of limited public health capacity, many tools are...

Machine learning and multi-omics technologies for precision cardiovascular medicine: advancing diagnosis, risk prediction, and therapeutic guidance.

Cardiovascular disease remains a major global health burden. Owing to its complex pathogenesis and marked clinical heterogeneity, conventional one-size-fits-all strategies often yield limited benefit for a substantial proportion of patients. Precision medicine advocates individualized management based on patients' clinical and molecular characteristics to improve outcomes. In this context, multi-o...

Global research trends in perioperative pressure injury prevention: A bibliometric analysis from repositioning to technology-assisted strategies.

BACKGROUND: Perioperative pressure injuries remain a major patient safety challenge, particularly among critically ill and immobilised patients. Altho...

Planning the development of an AI-driven decision support architecture for the recognition of sudden cardiac arrest by 9-1-1 telecommunicators: report of a community engagement and brainstorming meeting.

OBJECTIVES: Sudden cardiac arrest is a leading cause of mortality in Canada (40,000 treatable deaths annually). Despite the benefits of 9-1-1 telecomm...

Healing Without Certainty: The Ethical Significance of Uncertainty in Israeli Medicine in the Age of Artificial Intelligence.

The growing integration of artificial intelligence into healthcare is frequently associated with efforts to reduce uncertainty through prediction, dat...

A multi-scale fusion model based on multi-phase contrast-enhanced CT for predicting pancreatic cancer resectability.

Purpose Develop a multi-scale fusion model (MSFM) based on multi-phase contrast-enhanced computed tomography (CECT) to predict pancreatic cancer (PC) ...

A Large Language Model-Based Simulation Protocol Using ChatGPT for Training Novice Critical Care Nurses in Family Crisis Communication and De-escalation.

High-stress conversations with family members in distress are a common part of the intensive care unit (ICU) nursing environment. Novice critical care...

Digital and Smart Technologies for Early Pressure Injury Detection and Prevention in Stroke and Mobility-Impaired Patients: A Scoping Review.

BACKGROUND: Pressure injuries remain a major complication among stroke and other mobility-impaired populations. Digital and smart technologies are inc...

Diagnostic decision-making, vertebral augmentation, and osteoporosis therapy in vertebral compression fractures: a narrative review.

Vertebral compression fractures (VCFs) represent the most prevalent osteoporotic fracture and constitute a growing cause of morbidity, mortality, and ...

Real-world analysis of depression-related adverse events associated with the adsorbed anthrax vaccine: integrating pharmacovigilance signals, machine learning risk prediction, and transcriptomic mechanisms.

BACKGROUND: Anthrax remains a life-threatening zoonotic disease in resource-limited settings. Adsorbed anthrax vaccine (AVA, BioThrax) is the only Uni...

Can ChatGPT pass the polish national medical specialization examination in orthopedics and traumatology?

INTRODUCTION: Artificial intelligence (AI) has evolved rapidly in recent years and is becoming increasingly integrated into many areas of medicine. In...

Selection and learning shape communication networks in the dog brain.

Over tens of thousands of years of coevolution with humans, dogs have developed exceptional communicative abilities through both inherited adaptations...

Ethical aspects of artificial intelligence use in neonatal intensive care units: a scoping review.

UNLABELLED: This study aims to map ethical, legal, social, professional, and implementation issues associated with artificial intelligence (AI) in neo...

Quantifying generalization error in machine learning prediction of cognitive decline.

BACKGROUND: Predicting cognitive decline as a continuum, from healthy age-related decline to mild cognitive impairment and dementia, enables more prec...

[Diagnostic efficacy and teaching value of artificial intelligence-assisted diagnostic systems in cervical liquid-based cytology screening].

Objective: To systematically evaluate the diagnostic performance of an artificial intelligence (AI)-assisted diagnostic system in identifying squamous...

Deep learning reveals a neurocomputational mechanism predicting depression risk in adolescents.

Early detection and prevention of psychiatric disorders, particularly depression, remain as major global health challenges, yet reliable tools for ide...

Impact of Artificial Intelligence Chatbots on Student Confidence and Perceptions in a Communication Course.

OBJECTIVES: To 1) improve pharmacy students' perceived confidence in communication skills and 2) identify perceptions of counseling a text-based AI-si...

Heterogeneous Associations Between Frequent Virtual Communication and Loneliness Among Older Adults: Observational Analysis.

BACKGROUND: Loneliness is a long-standing and widely acknowledged public health problem among older adults, yet evidence remains mixed regarding how v...

Exploring patients' and public perspectives on an oral capsule for gastric submucosal delivery in Denmark and the USA: a mixed-methods study protocol.

INTRODUCTION: Oral capsules for gastric submucosal delivery represent a fundamentally new route of administration for biologics, which are currently l...

Standardization of Retinal Vasculitis Terminology With Consensus Definitions From a Delphi Panel.

IMPORTANCE: Retinal vasculitis is a sight-threatening condition associated with diverse ocular and systemic diseases. Variability in terminology and d...