Cardiovascular

Strokes

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

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Human-in-the-Loop Myoelectric Pattern Recognition Control of an Arm-Support Robot to Improve Reaching in Stroke Survivors.

The objective of this study was to assess the feasibility and efficacy of using real-time human-in-t...

Controversy in Hypertension: Pro-Side of the Argument Using Artificial Intelligence for Hypertension Diagnosis and Management.

Hypertension presents the largest modifiable public health challenge due to its high prevalence, its...

Automated Identification of Stroke Thrombolysis Contraindications from Synthetic Clinical Notes: A Proof-of-Concept Study.

INTRODUCTION: Timely thrombolytic therapy improves outcomes in acute ischemic stroke. Manual chart r...

Multitarget Natural Compounds for Ischemic Stroke Treatment: Integration of Deep Learning Prediction and Experimental Validation.

Ischemic stroke's complex pathophysiology demands therapeutic approaches targeting multiple pathways...

Risk of bias assessment of post-stroke mortality machine learning predictive models: Systematic review.

BACKGROUND: Stroke is a major cause of mortality and permanent disability worldwide. Precise predict...

Compliance Evaluation with ChatGPT for Diagnosis and Treatment in Patients Brought to the ED with a Preliminary Diagnosis of Stroke.

OBJECTIVES: Chat Generative Pre-trained Transformer (ChatGPT) is a natural language processing produ...

A Novel Explainable Attention-Based Meta-Learning Framework for Imbalanced Brain Stroke Prediction.

The accurate prediction of brain stroke is critical for effective diagnosis and management, yet the ...

Prediction of Hypertension in the Pediatric Population Using Machine Learning and Transfer Learning: A Multicentric Analysis of the SAYCARE Study.

OBJECTIVE: To develop a machine learning (ML) model utilizing transfer learning (TL) techniques to p...

Intelligent risk stratification of hypertension based on ambulatory blood pressure monitoring and machine learning algorithms.

. Risk stratification of hypertension plays a crucial role in the treatment decisions and medication...

Development and validation of an interpretable machine learning model for predicting in-hospital mortality for ischemic stroke patients in ICU.

BACKGROUND: Timely and accurate outcome prediction is essential for clinical decision-making for isc...

Artificial intelligence in stroke rehabilitation: From acute care to long-term recovery.

Stroke is a leading cause of disability worldwide, driving the need for advanced rehabilitation stra...

Rapid Blood Clot Removal via Remote Delamination and Magnetization of Clot Debris.

Micro/nano-scale robotic devices are emerging as a cutting-edge approach for precision intravascular...

Rehabilitation training robot using mirror therapy for the upper and lower limb after stroke: a prospective cohort study.

BACKGROUND: This prospective cohort study was designed to investigate and compare the effectiveness ...

Dynamic Prediction and Intervention of Serum Sodium in Patients with Stroke Based on Attention Mechanism Model.

Abnormal serum sodium levels are a common and severe complication in stroke patients, significantly ...

How Can Robotic Devices Help Clinicians Determine the Treatment Dose for Post-Stroke Arm Paresis?

Upper limb training dose after stroke is usually quantified by time and repetitions. This study anal...

Deep Learning Enhanced Near Infrared-II Imaging and Image-Guided Small Interfering Ribonucleic Acid Therapy of Ischemic Stroke.

Small interfering RNA (siRNA) targeting the NOD-like receptor family pyrin domain-containing 3 (NLRP...

Separation of stroke from vestibular neuritis using the video head impulse test: machine learning models versus expert clinicians.

BACKGROUND: Acute vestibular syndrome usually represents either vestibular neuritis (VN), an innocuo...

Deep Learning-Based ASPECTS Algorithm Enhances Reader Performance and Reduces Interpretation Time.

BACKGROUND AND PURPOSE: ASPECTS is a long-standing and well-documented selection criterion for acute...

Interpretation of cardiopulmonary exercise test by GPT - promising tool as a first step to identify normal results.

BACKGROUND: Cardiopulmonary exercise testing (CPET) is used in the evaluation of unexplained dyspnea...

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