Head Trauma

tDCS synchronous robotic training on lower-limb with post-stroke hemiplegia: a comparative study between synchronous and sequential group.

BACKGROUND: This study was aimed to compare the effects of tDCS synchronized with robotic training(RT)and tDCS sequential followed by RT on lower-limb with post-stroke hemiplegia, thus to inform clinical decision-making between these delivery schedules. METHODS: 64 patients who met the inclusion and exclusion criteria were allocated into a synchronous group and a sequential group. The synchronous ...

A clinician-centered evaluation framework for large language models in patient education: Integrating the Technology Acceptance Model and Medical Condition Regard Scale.

Inadequate post-care patient education contributes to preventable readmissions and adverse outcomes that disproportionately affect medically complex, high-need communities. Large language models (LLMs) show promise for generating personalized, plain-language patient education at scale. However, existing LLM evaluation frameworks prioritize technical accuracy over patient accessibility and alignmen...

Deep Learning-guided Late-Phase Dynamic Frame Prediction for Accelerated Patlak Analysis in 18F-FDG-PET Brain Imaging.

PURPOSE: Dynamic 18F-FDG-PET enables the quantitative assessment of cerebral glucose metabolism but requires prolonged acquisition times, which pose c...

AI-based disease severity grading predicts complications in laparoscopic appendectomy.

BACKGROUND: Appendicitis severity underpins contemporary management guidelines, where laparoscopic appendectomy remains gold standard. Preoperative me...

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 limitations due to imbalances in the training data. Fo...

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 stress hyperglycaemia ratio (SHR), which adjusts ...

Integrative single-cell sequencing and machine learning analyses identify chronic inflammation and cancer-associated fibroblast subsets as drivers of adverse outcomes in ovarian cancer.

BACKGROUND: Ovarian cancer remains the deadliest gynecological malignancy, with neoadjuvant chemotherapy (NACT) often leaving residual fibroblast-enri...

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), but validation quality and clinical readiness rem...

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 whose null-space renders the reconstruction problem se...

Automated Post-Analytical Workflow for Newborn Screening Using a Hybrid Rule-Based and Retrieval-Augmented Large Language Model System.

Newborn screening using tandem mass spectrometry requires complex post-analytical workflows, including QC review, patient report generation, and cutof...

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 the field lacks clear, data-driven definitions of 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, substantially increasing patients' mortality and mor...

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 disorders and improve the delineation of lesions. H...

CKLF1 Serves as a Pivotal Mediator of Blood-Brain Barrier Disruption and Neuroinflammation via PI3K/AKT/mTOR Signaling in Ischemic Stroke.

Ischemic stroke (IS) is accompanied by blood-brain barrier (BBB) disruption and neuroinflammatory activation, but the upstream regulatory mechanisms r...

An AI-Supported Virtual Patient Application Using a Structured Prompting Framework to Develop Mental Status Examination Skills in Psychiatric Nursing Internship Students: An Interventional Mixed-Methods Study.

The aim of this study is to evaluate the effect of an artificial intelligence (AI)-powered virtual patient application (ChatGPT) on the development of...

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 professional football players with hamstring injuries u...

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 PTE-diseased state in our cohort.•Data-driven feat...

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 standard-dose images from low-dose images in brain MRI, b...

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

INTRODUCTION: Thrombocytopenia has heterogeneous mechanisms, including peripheral destruction, consumption, and reduced marrow production. This study ...