Neurology

Head Trauma

Latest AI and machine learning research in head trauma for healthcare professionals.

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Showing 169-189 of 6,666 articles
Machine-learning random forest algorithms predict post-cycloplegic myopic corrections from noncycloplegic clinical data.

SIGNIFICANCE: Machine learning random forest algorithms were used to predict objective refractive ou...

ADFQ-ViT: Activation-Distribution-Friendly post-training Quantization for Vision Transformers.

Vision Transformers (ViTs) have exhibited exceptional performance across diverse computer vision tas...

AI-MET: A deep learning-based clinical decision support system for distinguishing multisystem inflammatory syndrome in children from endemic typhus.

The COVID-19 pandemic brought several diagnostic challenges, including the post-infectious sequelae ...

Machine learning-based prediction of post-induction hypotension: identifying risk factors and enhancing anesthesia management.

BACKGROUND: Post-induction hypotension (PIH) increases surgical complications including myocardial i...

A novel generative model for brain tumor detection using magnetic resonance imaging.

Brain tumors are a disease that kills thousands of people worldwide each year. Early identification ...

Machine Learning Approaches to Prognostication in Traumatic Brain Injury.

PURPOSE OF REVIEW: This review investigates the use of machine learning (ML) in prognosticating outc...

Soft-tissue metastasis in esophageal cancer managed by dose escalation radiation therapy: a clinical case and review of literature.

Soft tissue metastasis in esophageal cancer is a very rare entity. A 76-year-old man was referred fo...

Identifying plastic materials in post-consumer food containers and packaging waste using terahertz spectroscopy and machine learning.

Accurate identification of plastic materials from post-consumer food container and packaging waste i...

Developing practical machine learning survival models to identify high-risk patients for in-hospital mortality following traumatic brain injury.

Machine learning (ML) offers precise predictions and could improve patient care, potentially replaci...

CT-based detection of clinically significant portal hypertension predicts post-hepatectomy outcomes in hepatocellular carcinoma.

BACKGROUND: While the CT-based method of detecting clinically significant portal hypertension (CSPH)...

Deep learning-based clustering for endotyping and post-arthroplasty response classification using knee osteoarthritis multiomic data.

OBJECTIVES: Primary knee osteoarthritis (KOA) is a heterogeneous disease with clinical and molecular...

Comparison of time-to-event machine learning models in predicting biliary complication and mortality rate in liver transplant patients.

Post-Liver transplantation (LT) survival rates stagnate, with biliary complications (BC) as a major ...

A Workflow-Efficient Approach to Pre- and Post-Operative Assessment of Weight-Bearing Three-Dimensional Knee Kinematics.

BACKGROUND: Knee kinematics during daily activities reflect disease severity preoperatively and are ...

Machine Learning-Based Pediatric Early Warning Score: Patient Outcomes in a Pre- Versus Post-Implementation Study, 2019-2023.

OBJECTIVES: To describe the deployment of pediatric Calculated Assessment of Risk and Triage (pCART)...

Constructing a machine learning model for systemic infection after kidney stone surgery based on CT values.

This study aims to develop a machine learning model utilizing Computed Tomography (CT) values to pre...

Development of clinical decision support for patients older than 65 years with fall-related TBI using artificial intelligence modeling.

BACKGROUND: Older persons comprise most traumatic brain injury (TBI)-related hospitalizations and de...

Identification of hub biomarkers in liver post-metabolic and bariatric surgery using comprehensive machine learning (experimental studies).

BACKGROUND: The global prevalence of non-alcoholic fatty liver disease (NAFLD) is approximately 30%,...

Using machine learning to predict outcomes following transcarotid artery revascularization.

Transcarotid artery revascularization (TCAR) is a relatively new and technically challenging procedu...

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