Head Trauma

Artificial intelligence-driven predictive analytics for postoperative management and recovery in trauma patients.

PURPOSE OF REVIEW: Post-traumatic care is evolving from a reactive, protocol-driven paradigm to a pr...

Exfoliated kidney cells from urine for non-invasive kidney transplant monitoring: A potential opportunity?

Kidney transplantation is usually the optimal treatment option for patients living with kidney failu...

Early Prediction of Adverse Stroke Outcomes using Non-clinical Factors and Missing Data: A Machine Learning Study.

Introduction Early prediction of stroke outcomes using prognostic tools may help clinical decision m...

Readability, Accuracy, and Lexical Diversity of New ChatGPT Models for Common Carpal Tunnel Syndrome Questions.

BACKGROUND: Carpal tunnel syndrome (CTS) is a prevalent neuropathy in hand surgery that significantl...

Radiography-based AI decision support for further post-traumatic knee MRI referral in children.

Developing and validating a machine learning model for predicting post-thrombolysis seizures in acute ischemic stroke.

Post-stroke seizures (PSS) manifests variably due to ischemic brain injury, yet its risk factors rem...

A fast fully automated approach for evaluating calcified lesions in intravascular ultrasound.

AIMS: Catheter-based coronary intervention is an effective treatment for acute coronary syndrome. Ho...

Prior beliefs & automated fact checking: Limits on the effectiveness of AI-based corrections.

Proliferation of misinformation poses significant challenges in contemporary society, necessitating ...

Pioneering the future: Delivering the first digitally generated CMC post-approval change dossier to global regulators simultaneously.

As medicinal products and their manufacturing processes evolve, biopharmaceutical companies must con...

Tailored psychotherapy and AI-enhanced contingency management for co-occurring disorders in cannabis use disorder: a systematic review.

BACKGROUND: Cannabis use disorder (CUD) commonly co-occurs with depression, post-traumatic stress di...

Post-secondary student adoption of mental health labels through their use of social media: a scoping review.

BACKGROUND: Social media is a significant source of information for post-secondary students, who are...

Artificial intelligence risk stratification from dynamic digital subtraction angiography radiomics predicts pulmonary embolism and associates with clinical outcomes in deep vein thrombosis: A retrospective cohort study.

OBJECTIVE: Current risk stratification for lower extremity deep vein thrombosis remains limited, oft...

Predicting Infant Sleep Patterns From Postpartum Maternal Mental Health Measures: Machine Learning Approach.

BACKGROUND: Postpartum maternal mental health (MMH) symptoms, including depression, anxiety, and chi...

Predicting Traumatic Brain Injury Post-Trauma Using Temporal Attention on Sleep-Wake Data.

BACKGROUND: Traumatic Brain Injury (TBI) is a major public health concern, and accurate classificati...

Graph Convolutional Networks Enable Fast Hemorrhagic Stroke Monitoring With Electrical Impedance Tomography.

OBJECTIVE: To develop a fast image reconstruction method for stroke monitoring with electrical imped...

A Shape and Size-Scaled Deep Learning Brain Injury Model for Near Real-Time Dynamic Impact Simulation.

Efficient deep learning brain injury models enable large-scale, strain-based investigations of traum...

Comprehensive benchmarking of deep learning approaches for automated astrocyte segmentation in traumatic brain injury.

Astrocyte morphological changes and GFAP upregulation are hallmarks of traumatic brain injury (TBI) ...

Monitoring the lateral ventricles in the presence of intracranial hemorrhage using automated dual segmentation.

BACKGROUND: Segmentation of intracranial hemorrhage (ICH) alongside the brain's ventricles can provi...

Explainable machine learning model for predicting traumatic brain injury-induced coagulopathy in elderly patients: A multicenter cohort study.

BACKGROUND: Traumatic brain injury-induced coagulopathy (TBI-IC) in the elderly is a severe complica...

Scanner-integrated reconstruction versus post-processing deep learning for low-count 18F-FDG PET/CT: a comparative clinical evaluation.

OBJECTIVES: To compare two deep learning (DL) approaches for low-count PET/CT: deep progressive reco...

Outcome Prediction in Pediatric Traumatic Brain Injury Utilizing Social Determinants of Health and Machine Learning Methods.

BACKGROUND AND PURPOSE: Considerable socioeconomic disparities exist among pediatric patients with t...