Head Trauma

Empirical Comparison and Analysis of Artificial Intelligence-Based Methods for Identifying Phosphorylation Sites of SARS-CoV-2 Infection.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a member of the large coronavirus family with high infectivity and pathogenicity and is the primary pathogen causing the global pandemic of coronavirus disease 2019 (COVID-19). Phosphorylation is a major type of protein post-translational modification that plays an essential role in the process of SARS-CoV-2-host interactions. The pre...

Reliability of post-contrast deep learning-based highly accelerated cardiac cine MRI for the assessment of ventricular function.

OBJECTIVE: The total examination time can be reduced if high-quality two-dimensional (2D) cine images can be collected post-contrast to minimize non-scanning time prior to late gadolinium-enhanced imaging. This study aimed to assess the equivalency of the pre-and post-contrast performance of 2D deep learning-based highly accelerated cardiac cine (DL cine) imaging by evaluating the image quality an...

Changes in serum concentration of perioperative inflammatory cytokines following the timing of surgery among mild-moderate traumatic brain injury patients and factors associated.

BACKGROUND: The safe timing window for surgery during the acute phase of inflammation due to traumatic brain injury (TBI) has not been studied extensi...

Machine Learning Reveals Demographic Disparities in Palliative Care Timing Among Patients With Traumatic Brain Injury Receiving Neurosurgical Consultation.

BACKGROUND: Timely palliative care (PC) consultations offer demonstrable benefits for patients with traumatic brain injury (TBI), yet their implementa...

Development and evaluation of a machine learning model for post-surgical acute kidney injury in active infective endocarditis.

INTRODUCTION: Acute kidney injury (AKI) is notably prevalent after cardiac surgery for patients with active infective endocarditis. This study aims to...

Diverse regulated cell death patterns and immune traits in kidney allograft with fibrosis: a prediction of renal allograft failure based on machine learning, single-nucleus RNA sequencing and molecular docking.

Post-transplant allograft fibrosis remains a challenge in prolonging allograft survival. Regulated cell death has been widely implicated in various k...

Reliability and quality of information provided by artificial intelligence chatbots on post-contrast acute kidney injury: an evaluation of diagnostic, preventive, and treatment guidance.

OBJECTIVE: The aim of this study was to evaluate the reliability and quality of information provided by artificial intelligence chatbots regarding the...

Deep learning methods for 3D magnetic resonance image denoising, bias field and motion artifact correction: a comprehensive review.

Magnetic resonance imaging (MRI) provides detailed structural information of the internal body organs and soft tissue regions of a patient in clinical...

Rapid detection of poultry meat quality using S-band to KU-band radio-frequency waves combined with machine learning-A proof of concept.

Rapid changes in consumer preferences for high-quality animal-based protein have driven the poultry industry to identify non-invasive, in-line process...

Predicting Epidural Hematoma Expansion in Traumatic Brain Injury: A Machine Learning Approach.

IntroductionTraumatic brain injury (TBI) is a leading cause of disability and mortality worldwide, with epidural hematoma (EDH) being a severe consequ...

Computer tomography-based radiomics combined with machine learning for predicting the time since onset of epidural hematoma.

Estimation of the age of epidural hematoma (EDH) is a challenge in clinical forensic medicine, and this issue has yet to be conclusively resolved. The...

Optimizing early diagnosis by integrating multiple classifiers for predicting brain stroke and critical diseases.

Machine learning has gained attention in the medical field. Continuous efforts are being made to develop robust models for early prognosis purposes. T...

Random Forest Prognostication of Survival and 6-Month Outcome in Pediatric Patients Following Decompressive Craniectomy for Traumatic Brain Injury.

BACKGROUND: There is a dearth of literature regarding prognostic and predictive factors for outcome following pediatric decompressive craniectomy (DC)...

An ANN models cortical-subcortical interaction during post-stroke recovery of finger dexterity.

Finger dexterity, and finger individuation in particular, is crucial for human movement, and disruptions due to brain injury can significantly impact ...

Comprehensive assessment of cascading dams-induced hydrological alterations in the lancang-mekong river using machine learning technique.

The development of cascading hydropower dams in river basins has significantly altered natural flow regimes in recent decades. This study investigates...

Explainable machine learning for early prediction of sepsis in traumatic brain injury: A discovery and validation study.

BACKGROUND: People with traumatic brain injury (TBI) are at high risk for infection and sepsis. The aim of the study was to develop and validate an ex...

Unreal that feels real: artificial intelligence-enhanced augmented reality for treating social and occupational dysfunction in post-traumatic stress disorder and anxiety disorders.

Fear- and trauma-related conditions, such as post-traumatic stress disorder (PTSD) and social phobia, often manifest as socially avoidant behaviours,...

The infection post flexible UreteroreNoscopy (I-FUN) predictive model based on machine learning: a new clinical tool to assess the risk of sepsis post retrograde intrarenal surgery for kidney stone disease.

PURPOSE: To create a machine-learning model for estimating the likelihood of post-retrograde intrarenal surgery (RIRS) sepsis.

Active Machine Learning for Pre-procedural Prediction of Time-Varying Boundary Condition After Fontan Procedure Using Generative Adversarial Networks.

The Fontan procedure is the definitive palliation for pediatric patients born with single ventricles. Surgical planning for the Fontan procedure has e...

Machine learning-based assessment of regional-scale variation of landslide susceptibility in central Vietnam.

Recurrent landslide events triggered by typhoons and tropical storms over Vietnam pose a longstanding threat to the nation's population and infrastruc...