Public Health & Policy

Clinical Trials

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

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Machine learning to phenotype pain and predict response to pain interventions among young adults with irritable bowel syndrome

Irritable bowel syndrome (IBS) is a prevalent disorder whose most debilitating symptom is pain. The complex, multifactorial nature of IBS pain leads to highly variable and often inadequate responses to self-management, underscoring the urgent need for personalized prediction models. This ancillary analysis of a randomized controlled trial (NCT03332537) utilized data from 80 young adults with IBS. ...

A medical algorithmic audit framework for evaluating the safety, equity, and quality of an AI Scribe tool in a paediatric developmental assessment clinic

Any tool that can reduce the administrative burden on healthcare providers while preserving safe, accountable and high-quality medical documentation is of immense value both to healthcare institutions and consumers. The key question we need to answer is whether a prospective tool can reduce these burdens while maintaining (and, ideally, elevating) quality documentation standards. The goal of this ...

Clinical Usability of Generative Artificial Intelligence for MR Safety Advice

This study investigated whether readily available, generative AI models, could be used to answer MR safety queries as an MR Safety Expert (MRSE), with...

First-in-Human Study of a First-in-Class AI-Designed Monoclonal Antibody (GB-0669) Against the Conserved SARS-CoV-2 Spike S2 Stem Helix

Antibodies against the SARS-CoV-2 spike receptor-binding domain provided effective COVID-19 treatment until resistant variants emerged. GB-0669 is a h...

Spatial biomarker-driven deep learning model via digital pathology predicts response to PI3K inhibitor buparlisib in head and neck squamous cell carcinoma

Buparlisib, a pan-class I PI3K inhibitor, combined with paclitaxel, demonstrated improved survival in the BERIL-1 trial for patients with recurrent/me...

Large Language Models for Detecting CONSORT Guideline Compliance in Published Randomized Clinical Trials: A Cross-Sectional Evaluation Study

Peer review processes may inadequately assess compliance with established reporting guidelines such as the Consolidated Standards of Reporting Trials ...

“Complex models, marginal benefits--a multi-centre development and validation study of early warning scores across 2·16 million patient admissions addressing intercurrent medical interventions”

The National Early Warning Score (NEWS) is a nationally recommended, clinically implemented system, used to prevent patient deterioration. While numer...

Lower pre-treatment TMS-evoked cortical reactivity and alpha-band oscillatory dynamics predict efficacy of primary motor cortex neuromodulation for chronic pain

Repetitive transcranial magnetic stimulation (rTMS) targeting the primary motor cortex (M1) provides significant pain relief in approximately 45% of p...

Prospective Evaluation of AI Risk Stratification for Triaging Expedited Screening Mammogram Interpretation

To prospectively evaluate the feasibility and performance of expedited screening mammogram interpretation for women identified as high-risk by a deep ...

Understanding the Relationship Between Germ Layer Origin and Cancer Therapy Response: A Systematic Review

Cancer therapeutic response patterns may be fundamentally influenced by embryonic germ layer origin. Emerging evidence suggests mesoderm-derived malig...

The Cognitive Safety Net: Comparing Human and AI Diagnostic Reasoning during Complex Clinical Situations

Diagnostic error in high-stakes clinical environments remains a significant cause of preventable harm. While a new generation of customisable digital ...

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 hallucinations and factual errors. Clinician revie...

PregMedNet: Multifaceted Maternal Medication Impacts on Neonatal Complications

While medication use is common among pregnant women, medication safety remains insufficiently characterized because studies in pregnant women are chal...

Arkangel AI, OpenEvidence, ChatGPT, Medisearch: are they objectively up to medical standards? A real-life assessment of LLMs in healthcare

Large language models (LLMs) are increasingly used in healthcare, but standardized benchmarks fail to capture their validity and safety in real-world ...

Beyond Accuracy: An Efficiency- and Safety-Aware Framework for Evaluating Clinical AI with Large Language Models

Large language models (LLMs) demonstrate strong performance on medical reasoning tasks, but current evaluation approaches focus primarily on accuracy,...

Machine Learning Analysis of Routine EEG Accurately Predicts Anti-Seizure Medication Response

Despite the availability of more than 20 anti-seizure medications (ASMs), approximately half of patients with newly diagnosed epilepsy fail their firs...

Oxytocin Enhances Social-Emotional Reciprocity in Autism

We evaluated whether oxytocin improves social-emotional reciprocity in children and adolescents with autism spectrum disorder (ASD) by conducting a se...

Leveraging simulation to provide a practical framework for assessing the novel scope of risk of LLMs in healthcare

Large language models (LLMs) are rapidly entering clinical care, yet their definitionally probabilistic outputs have delivered a variety of grossly un...

Automated Video-Based Analysis of Surgical Meta-competencies Using Computer Vision

Traditional surgical training relies on an apprenticeship model, which is subjective and threatened by human bias. Performance metric scales attempt t...

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