Neurology

Head Trauma

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

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Investigation of Machine Learning Approaches for Traumatic Brain Injury Classification via EEG Assessment in Mice.

Due to the difficulties and complications in the quantitative assessment of traumatic brain injury (...

Unsupervised Machine Learning Reveals Novel Traumatic Brain Injury Patient Phenotypes with Distinct Acute Injury Profiles and Long-Term Outcomes.

The heterogeneity of traumatic brain injury (TBI) remains a core challenge for the success of interv...

Detection of Moderate Traumatic Brain Injury from Resting-State Eye-Closed Electroencephalography.

Traumatic brain injury (TBI) is one of the injuries that can bring serious consequences if medical a...

Ga-PSMA PET/CT versus CT and bone scan for investigation of PSA failure post radical prostatectomy.

OBJECTIVE: To evaluate the use of Gallium-68 prostate-specific membrane antigen positron emission to...

Convolutional neural network enhancement of fast-scan low-dose cone-beam CT images for head and neck radiotherapy.

To improve image quality and CT number accuracy of fast-scan low-dose cone-beam computed tomography ...

Prediction of Early TBI Mortality Using a Machine Learning Approach in a LMIC Population.

In a time when the incidence of severe traumatic brain injury (TBI) is increasing in low- to middle...

Endocannabinoid degradation inhibitors ameliorate neuronal and synaptic alterations following traumatic brain injury.

Our previous work showed that lateral fluid percussion injury to the sensorimotor cortex (SMC) of an...

Training and Validation of Deep Neural Networks for the Prediction of 90-Day Post-Liver Transplant Mortality Using UNOS Registry Data.

Prediction models of post-liver transplant mortality are crucial so that donor organs are not alloca...

A lesson in implementation: A pre-post study of providers' experience with artificial intelligence-based clinical decision support.

BACKGROUND: To explore attitudes about artificial intelligence (AI) among staff who utilized AI-base...

Effects of post-weaning supplementation of immunomodulatory feed ingredient on body weight and cortisol concentrations in program-fed beef heifers.

The objective of this study was to determine the effects of an immunomodulatory feed ingredient duri...

Intracatheter Tissue Plasminogen Activator for Chronic Subdural Hematomas after Failed Bedside Twist Drill Craniostomy: A Retrospective Review.

Introduction Chronic subdural hematomas (cSDH) are common in neurosurgery with various symptoms and ...

Machine learning for the detection of early immunological markers as predictors of multi-organ dysfunction.

The immune response to major trauma has been analysed mainly within post-hospital admission settings...

A multi-path 2.5 dimensional convolutional neural network system for segmenting stroke lesions in brain MRI images.

Automatic identification of brain lesions from magnetic resonance imaging (MRI) scans of stroke surv...

Inactivation of on post-harvest cantaloupe and lettuce by a lytic bacteriophage cocktail.

() is a causative agent of multiple outbreaks of foodborne illness associated with fresh produce, i...

Machine learning-based dynamic mortality prediction after traumatic brain injury.

Our aim was to create simple and largely scalable machine learning-based algorithms that could predi...

The neural and neurocomputational bases of recovery from post-stroke aphasia.

Language impairment, or aphasia, is a disabling symptom that affects at least one third of individua...

Fuzzy logic-based clinical decision support system for the evaluation of renal function in post-Transplant Patients.

OBJECTIVES: In the context of the gradual development of artificial intelligence in health care, the...

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