Prevention of medical errors

Harnessing artificial intelligence for pediatric health: Current trends and future opportunities.

Artificial intelligence (AI) is transforming pediatric healthcare, offering novel opportunities for early diagnosis, personalized treatment, and more efficient clinical workflows. However, its integration into children's health faces significant challenges due to the unique developmental, biological, and ethical considerations involved. This review explores how AI, leveraging large-scale real-worl...

AI for Hospital Infection Prevention and Control: Real-World Implementation, Impact, and the Gap Beyond Model Development.

BACKGROUND: Artificial intelligence and machine learning (AI/ML) may strengthen hospital infection prevention and control (IPC) through automated surveillance, early warning, and decision support, but the evidence base is fragmented and often limited to retrospective model development. METHODS: We conducted a PRISMA 2020 systematic review to synthesize studies of AI/ML in acute-care hospital IPC, ...

Using Generative Artificial Intelligence to Identify Central Line-associated Bloodstream Infections.

BACKGROUND: Central line-associated blood stream infection (CLABSI) surveillance is mandated and publicly reported in United States hospitals but requ...

Risk and protective factors in addictive behaviors: Integrating artificial intelligence and traditional analytical methods to assess social and psychological determinants.

PURPOSE OF REVIEW: Addictive behaviors, including both substance use disorders and behavioral addictions, arise from complex interactions among biolog...

Integrated High-Throughput Targeted Metabolomics and Machine Learning for Early Prediction and Prevention of Postoperative Delirium in Older Adult Surgical Patients: Prospective Multicenter Cohort Study.

BACKGROUND: Postoperative delirium (POD) is a common and severe complication in older adult patients with hip fracture, yet its pathogenesis remains u...

Artificial Intelligence-Powered Simulation for Telehealth Communication Training: Bridging Traditional Simulation and Artificial Intelligence.

INTRODUCTION: Traditional simulation-based communication training remains resource-intensive and difficult to scale. While artificial intelligence (AI...

[Pit and fissure morphology and its implication for caries prevention and treatment].

Dental caries is a chronic and progressive destruction of dental hard tissue under the combined action of multiple factors, with the pits and fissures...

Are We Listening or Just Delivering? A Critical Inquiry Into the Implementation Failures of Global Dental Reforms.

OBJECTIVES: Globally, dental reforms have gained momentum through enhanced policy dialogues, the rise of digital health, artificial intelligence and o...

Errors in AI-Transformed Patient-Centered Mental Health Documentation Written by Psychiatrists: Qualitative Pre-Post Study.

BACKGROUND: Patients' digital access to their personal health data is becoming increasingly common worldwide. However, medical documentation often con...

Cost-effectiveness of infection prevention and control measures for carbapenem-resistant Gram-negative bacilli: A systematic review protocol.

INTRODUCTION: Multidrug-resistant organisms, including carbapenem-resistant Gram-negative bacilli (CRGNB), have a heavy health and economic burden in ...

Assessing large language models in radiation risk communication: susceptibility, cultural-linguistic effects, and ethical reasoning.

PURPOSE: To assess the extent to which large language models (LLMs) amplify or attenuate inaccurate or contested narratives in radiation contexts and ...

Development of a community home-based dual-supplier cooperation care model for people with dementia based on an intelligent decision-assistance system: protocol of a 1-year randomised controlled trial in China.

INTRODUCTION: Dementia imposes significant care and financial burdens on families and countries globally. While high-quality home-based care is crucia...

Distributed trust-driven intelligence for edge-level prediction in mobile industrial internet of things.

Integrating innovative technologies with future networks enables significant advances in real-time distributed systems. The Industrial Internet of Thi...

Designing a children's health exposomics study protocol: The CHILDREN_FIRST multi-country prospective cohort using multi-omics and personalized prevention approaches.

Non-communicable diseases (NCDs) account for ~71% of all deaths globally, including 15 million premature deaths each year (deaths between 30-69 years ...

The Dark Side of Love: Prediction of Digital Intimate Partner Violence and Associated Factors Among University Students Using Machine Learning.

This study aimed to identify key risk factors and predict digital intimate partner violence (DIPV) exposure and perpetration among university students...

DARE: A Deformable Adaptive Regularization Estimator for learning-based medical image registration.

Deformable medical image registration is a fundamental task in medical image analysis. While deep learning-based methods have demonstrated superior ac...

Robust service migration for autonomous vehicles leveraging deep learning and cooperative V2V protocols.

Autonomous vehicles are essentially data centers on wheels. Between self-driving algorithms and high-definition mapping, the demand for instant proces...

Nurses' Lived Experiences of Generative Artificial Intelligence-Enabled Shift Handover Innovation: A Descriptive Phenomenological Study.

AIM: To explore nurses' lived experiences of a generative artificial intelligence-enabled shift handover innovation. DESIGN: A descriptive phenomenolo...

Responsible AI Integration Framework for Psychiatric Guidelines.

Artificial intelligence (AI) is reshaping medicine, promising advances in diagnosis, monitoring, and treatment, and psychiatry will be no exception. Y...

An interpretable machine learning model for predicting stroke in patients with hypertension: insights from the SPRINT.

Stroke is a leading cause of mortality worldwide, with hypertension being its most significant risk factor. However, few studies have specifically dev...