Cardiovascular

Strokes

Latest AI and machine learning research in strokes for healthcare professionals.

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Showing 2038-2058 of 3,943 articles
Native-Space 3D CarveMix for Multi-Site T1w Stroke Segmentation

Segmenting ischemic stroke lesions on T1-weighted (T1w) MRI acquired across different scanners and p...

An Imaging-Informed Reaction-Diffusion Model of Infarct Growth

Predicting final ischemic infarct volumes from acute imaging is a cornerstone of personalized stroke...

A Modular Agent for Reliable and Auditable Spatial Relation Verification in CT Scans

Reliable spatial understanding is an important prerequisite for future medical vision-language syste...

AsymFeX: A Symmetry-Driven Framework for Ischemic Stroke Segmentation Across Imaging Modalities and Stroke Stages

Fast and accurate segmentation of Acute Ischemic Stroke (AIS) lesions is essential for stroke progno...

Automated language impairment screening in acute stroke using connected speech

Connected speech is essential for everyday communication, but clinical constraints and patient fatig...

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ChartProbe: A Diagnostic Study on Visual Reasoning through Perception, Grounding, and Simple Reasoning

Vision-language models (VLMs) remain unreliable on chart questions that require reasoning over visua...

Perturbation-based Regional Interpretability through Subtraction Mapping (PRISM): naming-error dissociations in language models and post-stroke aphasia

Mechanistic interpretability of large language models lacks spatially resolved, falsifiable tools fo...

Bridging Online and Offline Handwriting via Differentiable Physical Rendering

Realistic handwritten text generation plays an important role in numerous applications, such as font...

FOUND-AF: Benchmarking ECG Foundation Models for Atrial Fibrillation Detection

Atrial fibrillation (AF) is the most common sustained cardiac arrhythmia and is associated with incr...

DiagLoop: A Counterfactual Data Flywheel with Stage-Localized Reinforcement for Diagnostic LLMs

Causal diagnostic models must explain how conclusions follow from evidence because diagnoses guide r...

Machine learning to detect intraoperative ischemia from electroencephalography in carotid endarterectomy surgery

Cerebral ischemia is a significant concern during high-risk surgeries, such as carotid endarterectom...

Hybrid novice-AI system achieves expert-level performance in intraoperative ischemia detection

Carotid endarterectomy carries the risk of intraoperative cerebral ischemia, which is monitored by e...

On the Efficacy of Self-Supervised Point Cloud Encoders for Efficient 3D Large Language Models

3D point cloud-language models (3D-LLMs) enable 3D understanding by pairing point cloud encoders wit...

FSB-Net: Frequency-Spatial Boundary Network for Brain Stroke Lesion Segmentation in Non-Contrast CT

Accurate segmentation of brain stroke lesions in non-contrast computed tomography (NCCT) scans is cr...

CardioMeta: Calibrated Multi-Task Prediction of Diabetes, Hypertension, and Cardiovascular Disease Across Population and EHR Data

Cardiometabolic diseases remain among the most persistent drivers of preventable morbidity because d...

Machine learning and data-driven models for predicting post-stroke dysphagia: a systematic review and meta-analysis

Background: Post-stroke dysphagia (PSD) contributes to aspiration, pneumonia, malnutrition, prolonge...

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