Neurology

Head Trauma

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

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Using swing resistance and assistance to improve gait symmetry in individuals post-stroke.

A major characteristic of hemiplegic gait observed in individuals post-stroke is spatial and tempora...

Jun 2015 26066783
Predictive modeling in pediatric traumatic brain injury using machine learning.

BACKGROUND: Pediatric traumatic brain injury (TBI) constitutes a significant burden and diagnostic c...

Mar 2015 25886156
Permutation entropy analysis of vital signs data for outcome prediction of patients with severe traumatic brain injury.

Permutation entropy is computationally efficient, robust to outliers, and effective to measure compl...

Nov 2014 25464358
Assist-as-Needed Robot-Aided Gait Training Improves Walking Function in Individuals Following Stroke.

A novel robot-aided assist-as-needed gait training paradigm has been developed recently. This paradi...

Oct 2014 25314703
Random Forest Model for Predicting Post-Lockdown Antenatal Depression Risk: A Cross-Sectional Study of Pregnant Women in China

Background As lockdown measures was eased, pregnant women faced an elevated risk of COVID-19 infecti...

JetViT: Efficient High-Resolution Vision Transformer with Post-Training Attention Search

We introduce JetViT, a novel family of hybrid-architecture Vision Transformer (ViT) models that matc...

Do Modern Post-Hoc Watermarking Methods Beat Broken-Arrows?

With the rapid proliferation of generative models, such as diffusion models, digital watermarking ha...

Post-ED Trajectory Prediction in Abdominal Pain with a Generative Medical Event Model

Importance: Abdominal pain causes roughly 10 million US emergency department (ED) visits annually, m...

Synaptic pruning, myelination and the emergence of psychiatric disorders in late adolescence

Adolescence is an important developmental period during which there are diverse changes in the brain...

A Conditional U-Net Pipeline with Pre- and Post-Processing for Aerial RGB-to-Thermal Image Translation

Paired RGB-thermal data has shown significant utility across a range of applications, including imag...

Predicting the When: Multimodal AI for Time-to-Recurrence Analysis After Atrial Fibrillation Ablation

Background: Catheter ablation is the most effective rhythm control strategy for atrial fibrillation ...

A Blood-Based Transcriptomic Signature for PTSD Classification Using Machine Learning

Post-traumatic stress disorder (PTSD) remains a significant psychiatric burden; despite growing biom...

Instruct-ICL: Instruction-Guided In-Context Learning for Post-Disaster Damage Assessment

Rapid and accurate situational awareness is essential for effective response during natural disaster...

Structural brain networks shape individual-level progression of brain atrophy after stroke

Stroke starts as a focal vascular lesion, but its structural consequences often extend beyond the le...

Reinforce Adjoint Matching: Scaling RL Post-Training of Diffusion and Flow-Matching Models

Diffusion and flow-matching models scale because pretraining is supervised regression: a clean sampl...

Risk-Controlled Post-Processing of Decision Policies

Predictive models are often deployed through existing decision policies that stakeholders are reluct...

Design and Implementation of BNN-Based Object Detection on FPGA

This paper implements a Binary Neural Network (BNN) based YOLOv3-tiny-like object detector on a low-...

SAIL: Structure-Aware Interpretable Learning for Anatomy-Aligned Post-hoc Explanations in OCT

Optical coherence tomography (OCT), a commonly used retinal imaging modality, plays a central role i...

Artificial Intelligence for Cardiac Biomarkers After Myocardial Infarction: A Systematic Review and a Leakage-Aware Modeling Framework

Aims To systematically evaluate how artificial intelligence and machine-learning (AI/ML) methods are...

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