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Prevention of medical errors

Latest AI and machine learning research in prevention of medical errors for healthcare professionals.

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Artificial Intelligence-Powered Precision Medicine for Cardiovascular Disease Prevention and Management

Artificial intelligence (AI) is transforming precision medicine, particularly in cardiovascular dise...

Development and validation of diagnostic and prognostic prediction tools for dental caries in young children: A protocol

Dental caries is the most common oral disease worldwide, affecting up to 90% of children globally. I...

Identifying profiles, trajectories, burden, social and biological factors in 3.3 million individuals with multimorbidity in England

Multimorbidity, the co-occurrence of multiple chronic conditions in an individual, has become a glob...

Kolmogorov-Arnold Network for Atherosclerotic Cardiovascular Disease Risk Prediction

Assessing the risk of future atherosclerotic cardiovascular disease (ASCVD) is crucial in clinical p...

Real-World Usage Patterns of Large Language Models in Healthcare

To characterize real-world LLM use by healthcare professionals and identify gaps between actual usag...

Large Language Models in Real-World Clinical Workflows: A Systematic Review of Applications and Implementation

Large language models (LLMs) offer promise for enhancing clinical care by automating documentation, ...

Lack of children in public medical imaging data points to growing age bias in biomedical AI

Artificial intelligence (AI) is rapidly transforming healthcare, but its benefits are not reaching a...

Longitudinal Prediction of BMI using Explainable AI: Integrating Polygenic Scores, Maternal, Early-Life and Familial Factors

This study aimed to predict body mass index (BMI) trajectories from childhood to early adulthood usi...

Beyond Accuracy: Multidimensional Evaluation of Large Language Models in Hepatocellular Carcinoma Management Emphasizing Prompting

Hepatocellular carcinoma is the most common type of primary liver cancer and remains a major global ...

Development of a novel musculoskeletal hypothesis using sparse Group Factor Analysis: the ADVANCE cohort

Musculoskeletal conditions are a leading global cause of disability, yet the factors influencing lon...

Evaluating anti-LGBTQIA+ medical bias in large language models

Large Language Models (LLMs) are increasingly deployed in clinical settings for tasks ranging from p...

External Validation of a Machine Learning Model to Predict Postpartum Hemorrhage in a US Northeastern Healthcare System

Postpartum hemorrhage (PPH) is a major cause of maternal morbidity and mortality. Timely prediction ...

Scoring Physician Risk Communication in Prostate Cancer Using Large Language Models

Effective risk communication is essential to shared decision-making in prostate cancer care. However...

Identifying Key Predictive Features for Opioid Use Disorder Using Machine Learning

Opioid Use Disorder (OUD) continues to pose a pressing public health challenge across the United Sta...

CardiacGPT™: A Real-Time AI Assistant for Intraoperative Guidance and Postoperative Decision Support in Cardiac Surgery

Cardiac surgery is one of the most complex and high-stakes areas of medicine, where intraoperative d...

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