Head Trauma

Flux dynamics and scenario simulation of PFAS under extreme hydrological perturbations in urban tributary flowing into the Yangtze River: A focus on floods.

Floods considerably amplify pollutant transfer into the Yangtze River (YZR) via tributaries. We explored flood-induced changes in PFAS pollution patterns and flux dynamics from urban tributaries into the YZR to assess the threats that floods pose to the water sources of the YZR. Concentrations of PFBA, PFOA, and PFHxA increased considerably during floods, increasing the total PFAS flux to 12,669 g...

Machine learning models in predicting viability after testicular torsion: a proof of concept study.

PURPOSE: Decision-making for orchiectomy following testicular torsion often relies on subjective clinical evaluations. This study investigates the efficacy of machine learning (ML) models in objectively predicting post-torsion testicular viability, aiming to maintain a parenchymal ratio over 80% compared to the contralateral testicle, irrespective of initial appearance and surgical timing. METHODS...

Machine learning in the development and application of patient-reported outcome measures (PROMs) for surgical patients: a systematic review.

BACKGROUND: Artificial intelligence (AI) and machine learning (ML) are increasingly integrated into healthcare, offering potential advancements in pat...

Mechanism-informed machine learning for individualized tacrolimus dose adjustment in the early post-kidney transplant period.

AIM: Tacrolimus dosing in the early post-kidney transplant period is challenging due to a narrow therapeutic index and substantial interindividual pha...

Clinical assessment of a Near-Infrared spectroscopy device for rapid triage in traumatic brain injury.

BACKGROUND: Traumatic Brain Injury (TBI) poses a significant public health challenge in India, with nearly 2 million cases annually and limited CT ava...

Superior machine learning model for post-cardiac arrest mortality prediction: a MIMIC-IV cohort study.

BACKGROUND: Post-cardiac arrest syndrome carries substantial mortality despite advances in resuscitation. We developed a machine learning model to pre...

Bergenin attenuates traumatic brain injury via inhibition of microglial PFKFB3-driven glycolytic-inflammatory crosstalk.

Traumatic brain injury (TBI) initiates a complex cascade of neuroinflammatory and metabolic disturbances that exacerbate neuronal loss and neurologica...

Predicting Cerebral Aneurysm Recurrence after Coil Embolization: A Novel Deep Learning Approach Using Time-of-flight Magnetic Resonance Angiography.

The recurrence of cerebral aneurysms after coil embolization remains a significant concern in clinical practice. This study introduced a novel approac...

An artificial intelligence-assisted automated quantitative evaluation system for condylar morphological changes of temporomandibular joint.

OBJECTIVES: To develop an artificial intelligence (AI)-assisted system for the automated quantitative evaluation of temporomandibular joint (TMJ) cond...

Rapid Point-of-Care Inflammatory Cytokine Monitoring during Normothermic Liver Perfusion via a Multiplexed Paper-Based Vertical Flow Assay.

The advent of normothermic machine perfusion (NMP) has substantially enhanced liver transplantation outcomes by enabling physiologic preservation and ...

Predicting emergency mortality risk in traumatic brain injury: comparative analysis of machine learning and large language model GPT-5.

BACKGROUND: Artificial intelligence (AI) has become increasingly important in predicting outcomes of traumatic brain injury (TBI). Traditional machine...

Development and validation of machine learning models to predict PTSD at multiple time points in hospitalized trauma patients.

BACKGROUND: Posttraumatic stress disorder (PTSD) is a severe trauma-related mental disorder with high global burden. Early identification remains chal...

Development and validation of interpretable machine learning models for dynamic prediction of prognosis in acute pancreatitis complicated by acute kidney injury: A multicenter study.

OBJECTIVE: This study aims to develop and validate interpretable machine learning (ML) models to dynamically predict mortality risk among intensive ca...

Post-Translational Modification Mediated By Acylation Modification Related Genes Induces Immunosuppression and Immunotherapy Resistance in Head and Neck Squamous Cell Carcinoma.

Acylation modification plays a crucial role in modulating head and neck squamous cell carcinoma (HNSCC) progression, and their specific prognostic imp...

Machine learning survival analysis for predicting kidney disease progression in patients with acute kidney injury undergoing continuous kidney replacement therapy: An analysis of the LINKA database.

PURPOSE: The progression of acute kidney injury (AKI) to end-stage kidney disease (ESKD) poses challenges due to high risks of comorbidities and poor ...

Graph attention network with comorbidity connectivity embedding for post-traumatic epilepsy risk prediction using sparse time-series electronic health records.

BACKGROUND: Traumatic brain injury (TBI) is a major risk factor for neurological disorders, including post-traumatic epilepsy (PTE), a debilitating co...

An explainable predictive machine learning model reveals ARRB2 as a key gene in post-traumatic stress disorder: A GEO database study.

A number of processes and pathways have been reported in the development of Post-Traumatic Stress Disorder (PTSD), however, novel biomarkers need to b...

TBC-ac4C: Identification of N4-acetylcytidine sites by incorporating TCN and BiGRU based on multi-head cross-attention mechanism.

N4-acetylcytidine (ac4C), a pivotal post-transcriptional modification, modulates mRNA lifecycle dynamics and is linked to numerous pathologies. Accura...

Automated interstitial lung abnormalities detection at CT: external validation and potential recognition of traction bronchiectasis/bronchiolectasis.

PURPOSE: An artificial intelligence (AI) system for detecting interstitial lung abnormalities (ILA) was previously developed but requires external val...

Machine Learning-Based Prediction for Axial Pain Following Expansive Unilateral Open-Door Laminoplasty: A Retrospective Cohort Study.

INTRODUCTION: Axial pain is a common complication following expansive unilateral open-door laminoplasty (ELAP); however, traditional statistical metho...