Cardiovascular

Strokes

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

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Using multiomic data to predict postoperative complications after major surgery in the UK Biobank cohort

Introduction Postoperative complications after major surgery have substantial impacts on morbidity a...

Evidential Perfusion Physics-Informed Neural Networks with Residual Uncertainty Quantification

Physics-informed neural networks (PINNs) have shown promise in addressing the ill-posed deconvolutio...

CRESTomics: Analyzing Carotid Plaques in the CREST-2 Trial with a New Additive Classification Model

Accurate characterization of carotid plaques is critical for stroke prevention in patients with caro...

Frequency-dependent diffusion tensor distribution imaging in the evaluation of ischemic stroke

Non-invasive MRI is widely used to assess and monitor ischemic stroke, yet conventional approaches o...

Clinically-aligned ischemic stroke segmentation and ASPECTS scoring on NCCT imaging using a slice-gated loss on foundation representations

Rapid infarct assessment on non-contrast CT (NCCT) is essential for acute ischemic stroke management...

Machine learning-based prediction of cardiovascular disease risk in Africa using WHO Stepwise Surveys: 2014-2019

Introduction: Cardiovascular diseases (CVDs) are the leading cause of death globally, with rising bu...

From Blind Spots to Gains: Diagnostic-Driven Iterative Training for Large Multimodal Models

As Large Multimodal Models (LMMs) scale up and reinforcement learning (RL) methods mature, LMMs have...

Breaking Semantic-Aware Watermarks via LLM-Guided Coherence-Preserving Semantic Injection

Generative images have proliferated on Web platforms in social media and online copyright distributi...

AI-based Speech Error Detection to Differentiate Primary Progressive Aphasia Variants

Background: Artificial Intelligence (AI) based approaches to speech analysis have the potential to a...

Restoring brain-to-text communication in a person with dysarthria from pontine stroke using an intracortical brain-computer interface

Restoring communication for people with dysarthria secondary to pontine stroke remains a critical ch...

Prompting is All You Need: How to Make LLMs More Helpful for Clinical Decision Support

Importance: Large language models (LLMs) offer potential decision support, but their accuracy varies...

AI-Detected Asymptomatic Atrial Fibrillation and Risk of Incident Ischemic Stroke and Cardiovascular Events: A UK Biobank Study

Background: Advances in wearable devices and machine-learning-based ECG analysis enable highly accur...

Agentic Trial Emulation to Learn Health System-specific Drug Effects At Scale

Objective: Electronic Health Record (EHR)-based trial emulation can support translation of randomize...

The Sound of Death: Deep Learning Reveals Vascular Damage from Carotid Ultrasound

Cardiovascular diseases (CVDs) remain the leading cause of mortality worldwide, yet early risk detec...

AI-DRIVEN DIAGNOSIS OF NON-ALCOHOLIC FATTY LIVER DISEASE AND ASSOCIATED COMORBIDITIES

Non-alcoholic fatty liver disease (NAFLD) is a globally prevalent hepatic condition caused by the bu...

StrokeNeXt: A Siamese-encoder Approach for Brain Stroke Classification in Computed Tomography Imagery

We present StrokeNeXt, a model for stroke classification in 2D Computed Tomography (CT) images. Stro...

Formally Verifying and Explaining Sepsis Treatment Policies with COOL-MC

Safe and interpretable sequential decision-making is critical in healthcare, yet reinforcement learn...

In-Hospital Stroke Prediction from PPG-Derived Hemodynamic Features

The absence of pre-hospital physiological data in standard clinical datasets fundamentally constrain...

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