Strokes

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 need confirmation with magnetic resonance (MR) image for treatment decision-making. We retrospectively included the NCCT slices of 129 normal subjects and 546 ischemic stroke patients (onset < 12 h) with corresponding MR slices as reference standard from a prospective registry of Chang Gung Research Da...

Human-Robot Cooperative Strength Training Based on Robust Admittance Control Strategy.

A stroke is a common disease that can easily lead to lower limb motor dysfunction in the elderly. Stroke survivors can effectively train muscle strength through leg flexion and extension training. However, available lower limb rehabilitation robots ignore the knee soft tissue protection of the elderly in training. This paper proposes a human-robot cooperative lower limb active strength training ba...

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 person. When left untreated, a stroke can be fatal. Acc...

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 prediction of disability risk is crucial for subsequen...

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 hypertension risk assessment model. The aim of this study...

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 needs after stroke vary as a function of the stroke ex...

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 prediction models that could supersede traditionall...

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 the common cause of ischemic stroke. We evaluate th...

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 persistent impairments and loss of function. Both intensit...

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 of developing pregnancy-associated hypertension. ...

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

This review aims to recommend directions for future research on robotic biofeedback towards prompt post-stroke gait rehabilitation by investigating th...

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 stroke may improve upper limb function. For roboti...

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-grip exoskeleton robot (TIGER) and task-specific mot...

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 the management of surgical patients. However, bloo...

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 is a strong relationship between time clock and t...

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 analyze for widespread use and have lacked robust compar...

The Impact of Cognitive Impairment on Robot-Based Upper-Limb Motor Assessment in Chronic Stroke.

BACKGROUND: Chronic upper extremity motor deficits are present in up to 65% of stroke survivors, and cognitive impairment is prevalent in 46-61% of st...

Effectiveness of robot-assisted virtual reality mirror therapy for upper limb motor dysfunction after stroke: study protocol for a single-center randomized controlled clinical trial.

BACKGROUND: Upper limb motor dysfunction is a common sequela of stroke, and its clinical efficacy needs to be improved. This protocol describes a tria...

Prediction and evaluation of combination pharmacotherapy using natural language processing, machine learning and patient electronic health records.

Combination pharmacotherapy targets key disease pathways in a synergistic or additive manner and has high potential in treating complex diseases. Comp...

DeepCNAP: A Deep Learning Approach for Continuous Noninvasive Arterial Blood Pressure Monitoring Using Photoplethysmography.

Arterial blood pressure (ABP) monitoring may permit the early diagnosis and management of cardiovascular disease (CVD); however, existing methods for ...