Public Health & Policy

Health Policy

Latest AI and machine learning research in health policy for healthcare professionals.

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Evaluating an LLM-Assisted Workflow for Clinical Documentation: A Pilot Randomized Controlled Trial on Time and Quality

Large language models (LLMs) have been investigated for clinical documentation, with concerns about ...

Optimized Machine Learning Algorithms for the Classification and Diagnosis of Sleep Disorders

Sleep disorders, including insomnia and obstructive sleep apnea, affect millions of individuals worl...

A train-and-assist device that upskills novices to strengthen the workforce and expand diagnostic access

Artificial intelligence and automation technologies are displacing millions of workers across indust...

Breaking the Cost Barrier: How Quantization Enables Efficient Development and Deployment of LLMs for Public Healthcare

The clinical promise of Large Language Models (LLMs) is often unrealized due to pro-hibitive computa...

LLM-based Multi-Agent Collaboration for Abstract Screening towards Automated Systematic Reviews

Systematic reviews (SRs) are essential for evidence-based practice but remain labor-intensive, espec...

Accurate, Race-Free LDL-C Estimation in Non-Fasting Settings: A Machine-Learning Study in 3,477 Adults

Traditional LDL-C testing barriers—mandatory 9–12 hour fasting and inperson visits—disproportionatel...

An Artificial Intelligence Model for Detection of Heart Failure with Preserved Ejection Fraction: A Report from HeartShare Study

Heart failure with preserved ejection fraction (HFpEF) accounts for over half of all heart failure c...

LLM-Assisted Taxonomy and Temporal Analysis of Provider Questions About HIV in provider-to-provider telehealth

Ongoing education in HIV care is limited for many healthcare providers working in rural and non-acad...

Proprietary and Open-Source Large Language Models on the Korean Pharmacist Licensing Examination: A Comparative Benchmarking Study

Large language models (LLMs) have shown remarkable advancements in natural language processing, with...

Clustering high-cost patients in England using machine learning: a population-based cohort study

To identify clusters of high-cost patients in England based on diagnoses and sociodemographic charac...

Explainability in action: A metric-driven assessment of local explanations for healthcare tabular models

Explainable AI (XAI) is essential in clinical machine learning, yet quantitative evaluation of expla...

How Large Language Models Can Affect Clinical Reasoning: A Randomized Clinical Trial

LLMs have encoded a vast array of medical knowledge and are being integrated into clinical settings ...

A novel open access multimodal dataset of nodule imaging and circulating proteome from a lung cancer screening cohort

Low-dose computed tomography (LDCT) lung cancer screening has significantly enhanced early detection...

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