Public Health & Policy

Clinical Trials

Latest AI and machine learning research in clinical trials for healthcare professionals.

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Priorities for AI Education: Clinicians’ Perspectives

Educating clinicians about Artificial Intelligence (AI) is an urgent need(1) as the UK General Medical Council (GMC) places liability with practitioners(2) and the EU AI Act with employers to provide appropriate training(3), but also because AI, like any tool, requires training to use safely. NHSE Capability Framework provides guidance(4), but frontline clinicians’ perspectives are unknown so we s...

Evaluating the Impact of Authoritative and Subjective Cues on Large Language Model Reliability for Clinical Inquiries: An Experimental Study

Large Language Models (LLMs) show significant promise in medicine but are typically evaluated using neutral, standardized questions. In real-world scenarios, inquiries from patients, students, or clinicians are often framed with subjective beliefs or cues from perceived authorities. The impact of these non-neutral, noisy prompts on LLM reliability is a critical but understudied area. This study ai...

A Randomized-Clinical Trial of Two Ambient Artificial Intelligence Scribes: Measuring Documentation Efficiency and Physician Burnout

Ambient artificial intelligence (AI) scribes record patient encounters and generate visit notes almost instantaneously, representing a promising solut...

The Golgi Apparatus as an Arbiter of Oncofetal Reprogramming: A Systematic Review and Meta-Analysis Linking Embryonic Germ Layer Origin to the Post-Translational Modification Landscape of Cancer

Post-translational modifications (PTMs) represent a fourth dimension of the genetic code, orchestrated by the Golgi apparatus and central to the biolo...

A Clinically-Informed Framework for Evaluating Vision-Language Models in Radiology Report Generation: Taxonomy of Errors and Risk-Aware Metric

Recent advances in vision-language models (VLMs) have enabled automatic radiology report generation, yet current evaluation methods remain limited to ...

Development of an AI-enabled predictive model to identify the ‘sick child’ at a pediatric telemedicine and medication delivery service in Haiti

One of the most difficult challenges in pediatric telemedicine is to accurately discriminate between the ‘sick’ and ‘not sick’ child, especially in re...

AI-literacy training enhances physician-LLM diagnostic collaboration in a resource-limited setting: a randomized controlled trial

Diagnostic errors remain a pervasive yet preventable source of patient harm, with resourcelimited healthcare systems in low- and middle-income countri...

Effects of Parietal Cathodal tDCS during Game Cue Exposure on Internet Gaming Disorder: A Randomized Double-Blind Sham-Controlled Trial

Internet Gaming Disorder (IGD) is officially listed as a behavioral addiction, exhibits high prevalence and has inadequate treatment efficacy. Targeti...

A scoping review of the application of artificial intelligence for the analysis of adverse drug events in clinical research

The early detection of adverse drug events (ADEs) became a critical issue in clinical research after the thalidomide disaster in 1961, which resulted ...

Evaluating anti-LGBTQIA+ medical bias in large language models

Large Language Models (LLMs) are increasingly deployed in clinical settings for tasks ranging from patient communication to decision support. While th...

Prediction-powered Inference for Clinical Trials: application to linear covariate adjustment

Prediction-powered inference (PPI) [1] and its subsequent development called PPI++ [2] provide a novel approach to standard statistical estimation, le...

Artificial Intelligence-based Automated Echocardiographic Analysis and the Workflow of Sonographers: A randomized crossover trial

This randomized crossover trial aimed to evaluate whether an artificial intelligence (AI)-based automatic analysis tool for echocardiography could imp...

Personalized, closed-loop deep brain stimulation for chronic pain

Chronic pain is a major healthcare problem associated with maladaptive brain circuit changes - many patients are unresponsive to all available therapi...

AI-Powered Triage of Suicidal Ideation in Adolescents: A Comparative Evaluation of Large Language Models Using Synthetic Clinical Vignettes

To evaluate the performance of leading Large Language Models (LLMs) in classifying suicide risk and generating clinically appropriate action plans for...

A Novel Playbook for Pragmatic Trial Operations to Monitor and Evaluate Ambient Artificial Intelligence in Clinical Practice

Ambient artificial intelligence (AI) offers the potential to reduce documentation burden and improve efficiency through clinical note generation. Wide...

Classifying Adverse Events from SOAP Notes and Sensor Features in a Clinical Trial of Older Adults

Early detection of adverse events and fall injuries may improve patient safety outcomes for clinical trials in geriatric populations. This study evalu...

Impact of LLM Assistance on Physician Decision-Making: A Multi-Country Randomized Controlled Trial∗

Disparities in the quality of healthcare persist globally, with poor-quality care contributing significantly to preventable mortality, particularly in...

Artificial Intelligence-Guided Molecular Determinants of PI3K Pathway Alterations in Early-Onset Colorectal Cancer Among High-Risk Groups Receiving FOLFOX

Early-onset colorectal cancer (EOCRC), defined as diagnosis before age 50, is rising rapidly and disproportionately affects high-risk populations, par...

Using transportability methods to map the local effectiveness of mass drug administration for malaria in Senegal

Numerous trials have evaluated the effectiveness of mass drug administration (MDA) to rapidly reduce malaria transmission, but it is unknown whether e...

Early Subtypes and Progressions of Progressive Supranuclear Palsy: A Data-Driven Brain Bank Study

Progressive supranuclear palsy (PSP) is typically characterized by vertical supranuclear gaze palsy and early falls, referred to as Richardson’s syndr...

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