Head Trauma

ChatGPT-4o for Endoscopic Differentiation of Autoimmune Gastritis From Helicobacter pylori-Associated Atrophic Gastritis: A Post Hoc Head-to-Head Comparison With Specialized Deep Learning.

Large Language Models for Optimizing Patient Recruitment Decisions in Voice Data Generation Projects.

OBJECTIVES: Past studies have shown that many clinical machine learning models have performance limi...

Stress hyperglycaemia ratio and post-operative delirium after cardiac surgery: a retrospective cohort study of the MIMIC-IV database.

BACKGROUND: Post-operative delirium is a serious neurocognitive complication of cardiac surgery. The...

AI Models for Predicting Acute Kidney Injury (AKI) and Post-AKI Mortality: Systematic Review and Meta-Analysis.

BACKGROUND: Machine learning (ML) models are increasingly used to predict acute kidney injury (AKI),...

A physics-constrained Bayesian framework for QSM with uncertainty quantification and variational susceptibility source separation.

Quantitative Susceptibility Mapping (QSM) requires inversion of a convolutional dipole operator whos...

Toward precision mindfulness: Predicting mindfulness outcomes after Mindfulness-Based Stress Reduction using interpretable machine learning.

BACKGROUND: Mindfulness-based interventions are increasingly used to target transdiagnostic processe...

A data-driven approach to define the stages and patterns of neurological recovery after traumatic spinal cord injury.

BACKGROUND: Recovery after spinal cord injury (SCI) follows a complex and variable trajectory, yet t...

Identification of acute kidney injury after non-cardiac surgery by machine learning leveraging a large electronic health record database.

Post-operative acute kidney injury (PO-AKI) is a frequent complication after non-cardiac surgery, su...

Deep-Learning Based Contrast Boosting: A Multi-Center Multi-Reader Study on Clinical Performance With Standard Contrast Enhanced Brain MRI.

BACKGROUND: Gadolinium-based contrast agents are used in brain MRI to improve the visualization of d...

Clustering analysis of hamstring injuries-A pilot study to determine phenogroups based on injury characteristics and recovery duration.

PURPOSE: The objective of this pilot study was to determine clinically relevant phenogroups of profe...

Harnessing machine learning for functional connectivity-based feature discovery in post-traumatic epilepsy.

•Leakage-free nested CV-RFE identifies a reproducible connectivity signature that characterizes the ...

Evaluation of an AI-powered tool in improving lesion visualization on standard-dose contrast-enhanced brain MRI: a retrospective, multicenter study.

BACKGROUND AND PURPOSE: Artificial intelligence (AI) algorithms have been used to synthesize standar...

Unsupervised Global CBC/RUO/CPD Phenotyping Identifies Haematological Clusters Enriched for Thrombocytopenia Severity and Mechanisms.

INTRODUCTION: Thrombocytopenia has heterogeneous mechanisms, including peripheral destruction, consu...

rs57494551 increases CXCR5 expression and IgM+ CXCR5+ B-cell infiltration in the portal area of primary biliary cholangitis.

BACKGROUND: Primary biliary cholangitis (PBC) is a chronic, progressive, cholestatic liver disease c...

The Open Data Commons for Traumatic Brain Injury: An Interagency Community Platform for Pre-Clinical Data Management and Sharing.

The Open Data Commons for Traumatic Brain Injury (ODC-TBI.org) was launched in 2018 to support data ...

Risk analysis and warning model of post-noncardiac surgery acute kidney injury: A retrospective observational study.

Postoperative acute kidney injury (PO-AKI) following noncardiac surgery remains a major clinical cha...

Genome-Wide Association, Polygenic Risk Scores, and Machine Learning for Chronic Post-Surgical Pain Risk Stratification: A UK Biobank Study.

Chronic post-surgical pain is a prevalent and debilitating complication following surgery, represent...

Impact of Artificial Intelligence Chatbots on Student Confidence and Perceptions in a Communication Course.

OBJECTIVES: To 1) improve pharmacy students' perceived confidence in communication skills and 2) ide...

Predicting Readmissions or Post-Discharge Mortality After Cardiac Surgery with Machine Learning Using an Australian Database.

AIM: This study aimed to create machine learning algorithms using the Australian & New Zealand Socie...

PLM-ArgMe: Protein language model for arginine methylation prediction for different species.

Protein methylation is a crucial post-translational modification (PTM) responsible for many diseases...

Machine learning-based screening tool for predicting the risk of oropharyngeal dysphagia in patients with ischemic stroke.

PURPOSE: Dysphagia frequently complicates recovery after stroke, necessitating effective predictive ...