Cardiovascular

Strokes

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

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Showing 946-966 of 3,008 articles
Retrospective study of deep learning to reduce noise in non-contrast head CT images.

PURPOSE: Presented herein is a novel CT denoising method uses a skip residual encoder-decoder framew...

A Tenodesis-Induced-Grip exoskeleton robot (TIGER) for assisting upper extremity functions in stroke patients: a randomized control study.

PURPOSE: This study was aimed toward developing a lightweight assisting tenodesis-induced-grip exosk...

Diagnostic test accuracy of artificial intelligence analysis of cross-sectional imaging in pulmonary hypertension: a systematic literature review.

OBJECTIVES: To undertake the first systematic review examining the performance of artificial intelli...

Claims-based algorithms for common chronic conditions were efficiently constructed using machine learning methods.

Identification of medical conditions using claims data is generally conducted with algorithms based ...

Deep Learning to Decipher the Progression and Morphology of Axonal Degeneration.

Axonal degeneration (AxD) is a pathological hallmark of many neurodegenerative diseases. Deciphering...

Predicting the Risk of Hypertension Based on Several Easy-to-Collect Risk Factors: A Machine Learning Method.

Hypertension is a widespread chronic disease. Risk prediction of hypertension is an intervention tha...

Risk prediction of clinical adverse outcomes with machine learning in a cohort of critically ill patients with atrial fibrillation.

Critically ill patients affected by atrial fibrillation are at high risk of adverse events: however,...

Automated Collateral Flow Assessment in Patients with Acute Ischemic Stroke Using Computed Tomography with Artificial Intelligence Algorithms.

BACKGROUND: Collateral circulation is associated with improved functional outcome in patients with l...

Home-based self-help telerehabilitation of the upper limb assisted by an electromyography-driven wrist/hand exoneuromusculoskeleton after stroke.

BACKGROUND: Most stroke survivors have sustained upper limb impairment in their distal joints. An el...

ECG data dependency for atrial fibrillation detection based on residual networks.

Atrial fibrillation (AF) is an arrhythmia that can cause blood clot and may lead to stroke and heart...

A network of core and subtype-specific gene expression programs in myositis.

Myositis comprises a heterogeneous group of skeletal muscle disorders which converge on chronic musc...

Deep Learning-Based Automated Thrombolysis in Cerebral Infarction Scoring: A Timely Proof-of-Principle Study.

BACKGROUND AND PURPOSE: Mechanical thrombectomy is an established procedure for treatment of acute i...

MTANS: Multi-Scale Mean Teacher Combined Adversarial Network with Shape-Aware Embedding for Semi-Supervised Brain Lesion Segmentation.

The annotation of brain lesion images is a key step in clinical diagnosis and treatment of a wide sp...

Machine learning models of ischemia/hemorrhage in moyamoya disease and analysis of its risk factors.

OBJECT: This study aimed to determine the risk factors of ischemic/hemorrhagic stroke in patients su...

Deep Learning-Based Image Automatic Assessment and Nursing of Upper Limb Motor Function in Stroke Patients.

This paper mainly introduces the relevant contents of automatic assessment of upper limb mobility af...

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