Clinical Trials

The expression level of CACNA1C-encoded CaV1.2 is a tipping point between promotion and inhibition of dendritic growth in neurons

The CACNA1C gene encodes the CaV1.2 L-type voltage-gated calcium channel, which plays a crucial role in neuronal signaling. CACNA1C is a risk gene for psychiatric conditions involving disruption of neuronal connectivity such as schizophrenia, autism, and bipolar disorders. While genomic studies are consistently reinforcing the notion of CACNA1C as an important locus related to these diseases, the ...

Network Rerouting Under Ayahuasca: Temporally and Hemisphere-Resolved EEG Connectomics

Ayahuasca profoundly alters conscious experience, yet robust, time-resolved EEG markers of its network-level effects remain limited. We combined machine learning with complex-network analysis to quantify how functional connectivity reorganizes across time and hemispheres in resting-state EEG from a randomized, double-blind, placebo-controlled trial including three 5-min sessions: pre-dose (T1), 2 ...

Protocol for the development and validation of machine-learning models for predicting the risk of hypertriglyceridemia in critically ill patients receiving propofol sedation using retrospective data

Propofol is a widely used sedative-hypnotic agent for critically-ill patients requiring invasive mechanical ventilation (IMV). Despite its clinical be...

GLUCOSE: A Distributional Reinforcement Learning Model for Optimal Glucose Control After Cardiac Surgery

This study introduces Glucose Level Understanding and Control Optimized for Safety and Efficacy (GLUCOSE), a distributional offline reinforcement lear...

Quantitative AI based on evolutionary computation and information theory combined with mathematical functions yields algorithmic RNA biomarkers from a randomized rheumatoid arthritis clinical trial, accurately predicting individual patient responses to anti-TNF treatment, to enable precision medicine

The routine derivation of novel biomarkers from therapeutic clinical trials to accurately predict individual patient’s responses, would be a significa...

A Scoping Review of Artificial Intelligence Applications in Clinical Trial Risk Assessment

Artificial intelligence (AI) is increasingly applied to clinical trial risk assessment, aiming to improve safety and efficiency. This scoping review a...

Predicting Car Accident Severity in Northwest Ethiopia: A Machine Learning Approach Leveraging Driver, Environmental, and Road Conditions

Car accidents in Northwest Ethiopia have significantly increased in severity, with increasing impacts on public safety. This study aims to predict car...

Leveraging Longitudinal Patient-Reported Outcomes Trajectories to Predict Survival in Non-Small-Cell Lung Cancer

Despite their potential, patient-reported outcomes (PROs) are often underutilized in clinical decision-making, especially when improvements in PROs do...

A pragmatic randomized controlled trial of artificial intelligence (AI)-based predictive analytics monitoring for early detection of clinical deterioration

This pragmatic randomized controlled trial aimed to assess the effect of a passive display of artificial intelligence (AI)-based predictive analytics ...

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 increased brain age gap. This gap serves as a biom...

SLaM Image Bank – a real-world diverse London cohort linking brain MRI to electronic mental health and dementia records for the development of clinical decision support tools using artificial intelligence

Rapid developments are occurring in artificial intelligence (AI) and machine learning (ML) applied to neuroimaging. To date, advances in this space ha...

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 therapeutic interventions. However, incomplete reporting ...

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 inefficiencies in nursing workflows related to electronic he...

Computational Phenomapping of Randomized Clinical Trials to Enable Assessment of their Real-world Representativeness and Personalized Inference

Randomized clinical trials (RCTs) define evidence-based medicine, but quantifying their generalizability to real-world patients remains challenging. W...

VR-based Gamma Sensory Stimulation: A feasibility study

Alzheimer’s disease (AD) presents a critical global health challenge, with current therapies offering limited efficacy and safety in halting disease p...

Benchmarking And Datasets For Ambient Clinical Documentation: A Scoping Review Of Existing Frameworks And Metrics For AI-Assisted Medical Note Generation

The increasing adoption of ambient artificial intelligence (AI) scribes in healthcare has created an urgent need for robust evaluation frameworks to a...

Alignment of Large Language Models in Solving Medical Ethical Dilemmas

Deontology and utilitarianism are two philosophical approaches to ethical decision-making, often illustrated by the well-known “Trolley” dilemma. We e...

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. Analysis of data from these trials is a time-intensive...

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 factors increase the risk of developmental disabili...

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 effectiveness of a treatment can result in sub...