Public Health & Policy

Clinical Trials

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

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Brain Age Gap Reduction Following Physical Exercise Mirrors Negative Symptom Improvement in Schizophrenia Spectrum Disorders

Schizophrenia spectrum disorders (SSD) are associated with accelerated brain aging, reflected in an ...

SPIRIT-CONSORT-TM: a corpus for assessing transparency of clinical trial protocol and results publications

Randomized controlled trials (RCTs) can produce valid estimates of the benefits and harms of therape...

Introducing and Evaluating the Patient Report Template for AI-Powered Nursing Handoffs

This study evaluates the effectiveness of the Patient Report Template (PRT) in addressing inefficien...

VR-based Gamma Sensory Stimulation: A feasibility study

Alzheimer’s disease (AD) presents a critical global health challenge, with current therapies offerin...

Alignment of Large Language Models in Solving Medical Ethical Dilemmas

Deontology and utilitarianism are two philosophical approaches to ethical decision-making, often ill...

The Rise of the Large Language Models (LLMs): Can They Truly Match Clinical and Data Science Experts in Clinical Trial Data Analysis?

Clinical trials provide evidence of the efficacy and safety of experimental treatment regimens. Anal...

Uncovering distinct motor development trajectories in infants during the first half year of life

Infants undergo significant developmental changes in the first few months of life. While some risk f...

Advancing the prediction and understanding of placebo responses in chronic back pain using large language models

Placebo analgesia in chronic pain is a widely studied clinical phenomenon, where expectations about ...

The role of artificial intelligence in the application of the integrated electronic health records and patient-generated health data

This scoping review aims to identify and understand the role of artificial intelligence in the appli...

Integrated Explainable Ensemble Machine Learning Prediction of Injury Severity in Agricultural Accidents

Agricultural injuries remain a significant occupational hazard, causing substantial human and econom...

A Framework to Assess Clinical Safety and Hallucination Rates of LLMs for Medical Text Summarisation

Integrating large language models (LLMs) into healthcare settings can improve workflow efficiency an...

NutriRAG: Unleashing the Power of Large Language Models for Food Identification and Classification through Retrieval Methods

This study explores the use of advanced Natural Language Processing (NLP) techniques to enhance food...

Evaluating biomedical feature fusion on machine learning’s predictability and interpretability of COVID-19 severity types

Accurately differentiating severe from non-severe COVID-19 clinical types is critical for the health...

Transport-based transfer learning on Electronic Health Records: Application to detection of treatment disparities

Electronic Health Records (EHRs) sampled from different populations can introduce unwanted bi-ases, ...

Exploring the Potential of Large Language Models for Automated Safety Plan Scoring in Outpatient Mental Health Settings

The Safety Planning Intervention (SPI) produces a plan to help manage patients’ suicide risk. High-q...

A Deep Learning Framework for Causal Inference in Clinical Trial Design: The CURE AI Large Clinicogenomic Foundation Model

Clinical research is limited by the capability to define the most important combinations of clinical...

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