Strokes

Deep Learning in Ischemic Stroke Imaging Analysis: A Comprehensive Review.

Ischemic stroke is a cerebrovascular disease with a high morbidity and mortality rate, which poses a...

Machine learning based outcome prediction of large vessel occlusion of the anterior circulation prior to thrombectomy in patients with wake-up stroke.

PURPOSE: Outcome prediction of large vessel occlusion of the anterior circulation in patients with w...

Automatic identification of early ischemic lesions on non-contrast CT with deep learning approach.

Early ischemic lesion on non-contrast computed tomogram (NCCT) in acute stroke can be subtle and nee...

Deep learning-based behavioral profiling of rodent stroke recovery.

BACKGROUND: Stroke research heavily relies on rodent behavior when assessing underlying disease mech...

An Artificial Intelligence-Based Bio-Medical Stroke Prediction and Analytical System Using a Machine Learning Approach.

Stroke-related disabilities can have a major negative effect on the economic well-being of the perso...

Machine learning-based prediction of disability risk in geriatric patients with hypertension for different time intervals.

BACKGROUND: The risk of disability in older adults with hypertension is substantially high, and pred...

Evaluating the risk of hypertension in residents in primary care in Shanghai, China with machine learning algorithms.

OBJECTIVE: The prevention of hypertension in primary care requires an effective and suitable hyperte...

Reversing the Ruin: Rehabilitation, Recovery, and Restoration After Stroke.

PURPOSE OF REVIEW: Stroke is a common cause of disability in aging adults. A given individual's need...

Interpretable deep learning for the prognosis of long-term functional outcome post-stroke using acute diffusion weighted imaging.

Advances in deep learning can be applied to acute stroke imaging to build powerful and explainable p...

Automated detection of intracranial artery stenosis and occlusion in magnetic resonance angiography: A preliminary study based on deep learning.

BACKGROUND AND OBJECTIVES: Intracranial atherosclerotic stenosis of a major intracranial artery is t...

Revisiting dose and intensity of training: Opportunities to enhance recovery following stroke.

PURPOSE: Stroke is a global leading cause of adult disability with survivors often enduring persiste...

Robotic Biofeedback for Post-Stroke Gait Rehabilitation: A Scoping Review.

This review aims to recommend directions for future research on robotic biofeedback towards prompt p...

Development of early prediction model for pregnancy-associated hypertension with graph-based semi-supervised learning.

Clinical guidelines recommend several risk factors to identify women in early pregnancy at high risk...

Experiences of patients who had a stroke and rehabilitation professionals with upper limb rehabilitation robots: a qualitative systematic review protocol.

INTRODUCTION: Emerging evidence suggests that robotic devices for upper limb rehabilitation after a ...

Efficacy of Robots-Assisted Therapy in Patients With Stroke: A Meta-analysis Update.

BACKGROUND: Robot-assisted therapy (RAT) could address an unmet need to relieve the strain on health...

Internet of Things (IoT) Enables Robot-Assisted Therapy as a Home Program for Training Upper Limb Functions in Chronic Stroke: A Randomized Control Crossover Study.

OBJECTIVE: To compare the effects of using an Internet of things (IoT)-assisted tenodesis-induced-gr...

Hybrid robot-assisted gait training for motor function in subacute stroke: a single-blind randomized controlled trial.

BACKGROUND: Robot-assisted gait training (RAGT) is a practical treatment that can complement convent...

How do I/we forecast tomorrow's transfusion? A focus on recipients' profiles.

Red blood cell (RBC) transfusion is a life-saving medical intervention and has an essential role in ...

Multimodal data for systolic and diastolic blood pressure prediction: The hypertension conscious artificial intelligence.

Identifying acute ischemic stroke patients within the thrombolytic treatment window using deep learning.

BACKGROUND AND PURPOSE: Treatment of acute ischemic stroke is heavily contingent upon time, as there...

Utility of Normalized Body Composition Areas, Derived From Outpatient Abdominal CT Using a Fully Automated Deep Learning Method, for Predicting Subsequent Cardiovascular Events.

CT-based body composition (BC) measurements have historically been too resource intensive to analyz...