Neurology

Head Trauma

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

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Order-Based Bayesian Network Modeling of Early Detection and Post-Diagnosis Control for Cardiovascular Disease Risk in Type 2 Diabetes

Patients diagnosed with type 2 diabetes (T2D) are at increased risk of developing cardiovascular disease (CVD), the leading cause of morbidity and mortality in this population. Early detection and glycemic control within the first year after diagnosis reduce CVD risk. However, gaps remain in how to operationalize early detection of T2D using Electronic Health Record (EHR) data and quantify its rel...

MipSScs: Artificial neural network-based data integration of 2D/3D single-cell spatial RNA sequence data from virus-infected human cerebral organoids

There is interest in the use of recent single-cell spatial transcriptomic technologies to gain biological insights into disease mechanisms. Previously, we characterized the use of herpes simplex virus 1 (HSV-1) induced neuroinflammation in 2D dissociated cells from human cerebral organoids (dcOrgs) to model molecular and transcriptomic readouts associated with Alzheimers disease (AD). In this work...

Ride, Track, and Recover: Pilot Randomized Trial of a Wearable Digital Self-Management Intervention During a Veteran Endurance-Cycling Program

Post-traumatic stress disorder (PTSD) in veterans is characterized by persistent hyperarousal and comorbid anxiety and depressive symptoms that are di...

Jun 11 2026 2606.13529v1
Damage-TriageFormer: A Foundation-Model Framework for Typology-Based Building Damage Assessment from Mono-Temporal Imagery

Decision-relevant building damage assessment is critical for prioritizing resources and recovery after a disaster, yet most automated methods either f...

Jun 10 2026 2606.12248v1
Dissect and Prune: Enhancing Robustness in AI-Generated Image Detection

While existing AI-generated image detectors report high performance, we identify that this is largely driven by a critical prediction asymmetry: a bia...

Jun 9 2026 2606.10309v1
Building Change Detection in Earthquake: A Multi-Scale Interaction Network and A Change Detection Dataset

As one of the most destructive natural disasters, earthquakes have struck many countries around the world in recent years, causing serious economic lo...

Jun 9 2026 2606.10329v1
Multivariate Machine Learning Analysis of M-ECG-derived Heart Rate Variability in TBI Veterans, With and Without Comorbid PTSD

Traumatic brain injury (TBI) and posttraumatic stress disorder (PTSD) frequently co-occur in Veterans, producing overlapping symptoms and shared auton...

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 infection, potentially impacting their mental health. Thi...

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 match the accuracy of state-of-the-art full-attention ...

May 26 2026 2605.26636v1
Do Modern Post-Hoc Watermarking Methods Beat Broken-Arrows?

With the rapid proliferation of generative models, such as diffusion models, digital watermarking has emerged as a crucial solution for identifying AI...

May 26 2026 2605.27135v1
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, most resulting in discharge. Post-discharge courses...

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 and behavior. Goal-directed behaviors and the com...

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 image fusion, object tracking, and anomaly detection; ...

May 17 2026 2605.17564v1
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 (AF); however, recurrence remains common. Current ...

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

Post-traumatic stress disorder (PTSD) remains a significant psychiatric burden; despite growing biomarker research, no blood-based molecular diagnosti...

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

Rapid and accurate situational awareness is essential for effective response during natural disasters, where delays in analysis can significantly hind...

May 12 2026 2605.11439v1
Multimodal Wearable System for Objective Assessment of Dynamic Rotational Knee Biomechanics Following ACL Injury and Reconstruction: A Clinical Validation Study Using Ensemble Deep Learning

ABSTRACT Background The clinical assessment of knee stability after an Anterior Cruciate Ligament (ACL) injury is routinely conducted via operator-dep...

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 lesion site, resulting in distributed brain atrophy ...

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 sample is noised analytically, and a model regresses ag...

May 11 2026 2605.10759v1
Risk-Controlled Post-Processing of Decision Policies

Predictive models are often deployed through existing decision policies that stakeholders are reluctant to change unless a risk constraint requires in...

May 7 2026 2605.06479v1
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