Neurology

Head Trauma

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

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Showing 463-483 of 6,666 articles
Pulmonary contusion: automated deep learning-based quantitative visualization.

PURPOSE: Rapid automated CT volumetry of pulmonary contusion may predict progression to Acute Respir...

Deep learning in optical coherence tomography: Where are the gaps?

Optical coherence tomography (OCT) is a non-invasive optical imaging modality, which provides rapid,...

Deep Learning-Based Diagnosis of Fatal Hypothermia Using Post-Mortem Computed Tomography.

In forensic medicine, fatal hypothermia diagnosis is not always easy because findings are not specif...

Generating post-hoc explanations for Skip-gram-based node embeddings by identifying important nodes with bridgeness.

Node representation learning in a network is an important machine learning technique for encoding re...

An Empirical Comparison of Explainable Artificial Intelligence Methods for Clinical Data: A Case Study on Traumatic Brain Injury.

A longstanding challenge surrounding deep learning algorithms is unpacking and understanding how the...

A comprehensive dataset of annotated brain metastasis MR images with clinical and radiomic data.

Brain metastasis (BM) is one of the main complications of many cancers, and the most frequent malign...

Simulating complex patient populations with hierarchical learning effects to support methods development for post-market surveillance.

BACKGROUND: Validating new algorithms, such as methods to disentangle intrinsic treatment risk from ...

Deep learning prediction of post-SBRT liver function changes and NTCP modeling in hepatocellular carcinoma based on DGAE-MRI.

BACKGROUND: Stereotactic body radiation therapy (SBRT) produces excellent local control for patients...

Applications of artificial intelligence-machine learning for detection of stress: a critical overview.

Psychological distress is a major contributor to human physiology and pathophysiology, and it has be...

Deep learning based automated quantification of urethral plate characteristics using the plate objective scoring tool (POST).

INTRODUCTION: The plate objective scoring tool (POST) was recently introduced as a reproducible and ...

Assessing the utility of a sliding-windows deep neural network approach for risk prediction of trauma patients.

The risks of post trauma complications are regulated by the injury, comorbidities, and the clinical ...

Deep Learning-Enabled Morphometric Analysis for Toxicity Screening Using Zebrafish Larvae.

Toxicology studies heavily rely on morphometric analysis to detect abnormalities and diagnose diseas...

MIND-S is a deep-learning prediction model for elucidating protein post-translational modifications in human diseases.

We present a deep-learning-based platform, MIND-S, for protein post-translational modification (PTM)...

Multiplex Identification of Post-Translational Modifications at Point-of-Care by Deep Learning-Assisted Hydrogel Sensors.

Multiplex detection of protein post-translational modifications (PTMs), especially at point-of-care,...

The Current State of Susceptibility-Weighted Imaging and Quantitative Susceptibility Mapping in Head Trauma.

Susceptibility-weighted imaging (SWI) is a MR imaging technique suited to detect structural and micr...

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