Strokes

A Hybrid Stacked CNN and Residual Feedback GMDH-LSTM Deep Learning Model for Stroke Prediction Applied on Mobile AI Smart Hospital Platform.

Artificial intelligence (AI) techniques for intelligent mobile computing in healthcare has opened up...

A fuzzy logic-based approach for groundwater vulnerability assessment.

Groundwater vulnerability assessment systems have been developed to protect groundwater resources. T...

Deep Learning-based Assessment of Internal Carotid Artery Anatomy to Predict Difficult Intracranial Access in Endovascular Recanalization of Acute Ischemic Stroke.

BACKGROUND: Endovascular thrombectomy (EVT) duration is an important predictor for neurological outc...

Ultrafast MRI using deep learning echoplanar imaging for a comprehensive assessment of acute ischemic stroke.

OBJECTIVES: Acute ischemic stroke (AIS) is an emergency requiring both fast and informative MR seque...

Using Deep-Learning-Based Artificial Intelligence Technique to Automatically Evaluate the Collateral Status of Multiphase CTA in Acute Ischemic Stroke.

BACKGROUND: Collateral status is an important predictor for the outcome of acute ischemic stroke wit...

Effects of Upper Limb Robot-Assisted Rehabilitation Compared with Conventional Therapy in Patients with Stroke: Preliminary Results on a Daily Task Assessed Using Motion Analysis.

Robotic rehabilitation of the upper limb has demonstrated promising results in terms of the improvem...

Is the robotic rehabilitation that is added to intensive body rehabilitation effective for maximization of upper extremity motor recovery following a stroke? A randomized controlled study.

BACKGROUND: Trunk stabilization, which is a factor that directly affects the performance of affected...

Big Data in Stroke: How to Use Big Data to Make the Next Management Decision.

The last decade has seen significant advances in the accumulation of medical data, the computational...

External Validation of an Artificial Intelligence Device for Intracranial Hemorrhage Detection.

BACKGROUND: Artificial intelligence applications have gained traction in the field of cerebrovascula...

The effect of robot-assisted walking in different modalities on cardiorespiratory responses and energy consumption in patients with subacute stroke.

OBJECTIVES: The aim of our study was to evaluate the effect of robot-assisted walking in different m...

Overcoming Diagnostic Delays in Pulmonary Hypertension With Deep-Learning ECG Analysis.

Efficacy of Robot-Assisted Training on Rehabilitation of Upper Limb Function in Patients With Stroke: A Systematic Review and Meta-analysis.

OBJECTIVE: To systematically evaluate the effect of robot-assisted training (RAT) on upper limb func...

Analyzing the Relationship among Social Capital, Dynamic Capability, and Farmers' Cooperative Performance Using Lightweight Deep Learning Model: A Case Study of Liaoning Province.

The purpose of this study is to understand the relationship between social capital and the performan...

SAN-Net: Learning generalization to unseen sites for stroke lesion segmentation with self-adaptive normalization.

There are considerable interests in automatic stroke lesion segmentation on magnetic resonance (MR) ...

Automated in-depth cerebral arterial labelling using cerebrovascular vasculature reframing and deep neural networks.

Identifying the cerebral arterial branches is essential for undertaking a computational approach to ...

Dyspnea Severity Assessment Based on Vocalization Behavior with Deep Learning on the Telephone.

In this paper, a system to assess dyspnea with the mMRC scale, on the phone, via deep learning, is p...

Evaluating Fluency in Aphasia: Fluency Scales, Trichotomous Judgements, or Machine Learning.

BACKGROUND: Speech-language pathologists (SLPs) and other clinicians often use aphasia batteries, su...

Effects of Timed Frontal Plane Pelvic Moments During Overground Walking With a Mobile TPAD System.

Robotic gait training may improve overground ambulation for individuals with poor control over pelvi...

The use of machine learning and deep learning techniques to assess proprioceptive impairments of the upper limb after stroke.

BACKGROUND: Robots can generate rich kinematic datasets that have the potential to provide far more ...

Electrocardiogram Detection of Pulmonary Hypertension Using Deep Learning.

BACKGROUND: Pulmonary hypertension (PH) is life-threatening, and often diagnosed late in its course....

Effect of cyborg-type robot Hybrid Assistive Limb on patients with severe walking disability in acute stroke: A randomized controlled study.

OBJECTIVES: To investigate whether early gait training using Hybrid Assistive Limb (HAL) is feasible...