Strokes

Deep learning for multi-year ENSO forecasts.

Variations in the El Niño/Southern Oscillation (ENSO) are associated with a wide array of regional climate extremes and ecosystem impacts. Robust, long-lead forecasts would therefore be valuable for managing policy responses. But despite decades of effort, forecasting ENSO events at lead times of more than one year remains problematic. Here we show that a statistical forecast model employing a dee...

Can clinical audits be enhanced by pathway simulation and machine learning? An example from the acute stroke pathway.

OBJECTIVE: To evaluate the application of clinical pathway simulation in machine learning, using clinical audit data, in order to identify key drivers for improving use and speed of thrombolysis at individual hospitals.

Analysis of distance-based protein structure prediction by deep learning in CASP13.

This paper reports the CASP13 results of distance-based contact prediction, threading, and folding methods implemented in three RaptorX servers, which...

Technical considerations of multi-parametric tissue outcome prediction methods in acute ischemic stroke patients.

Decisions regarding acute stroke treatment rely heavily on imaging, but interpretation can be difficult for physicians. Machine learning methods can a...

Comprehensive analysis of efficient swimming using articulated legs fringed with flexible appendages inspired by a water beetle.

Drag-based swimming is usually accompanied with the shape change of rowing appendages to generate asymmetric force during the power stroke and recover...

The effect of using Gait Exercise Assist Robot (GEAR) on gait pattern in stroke patients: a cross-sectional pilot study.

: The Gait Exercise Assist Robot (GEAR) has been developed to support gait training for stroke patients. The GEAR can assist paretic lower limb swing ...

Deep regression neural networks for collateral imaging from dynamic susceptibility contrast-enhanced magnetic resonance perfusion in acute ischemic stroke.

PURPOSE: Acute ischemic stroke is one of the primary causes of death worldwide. Recent studies have shown that the assessment of collateral status cou...

Predicting Clinical Outcomes of Large Vessel Occlusion Before Mechanical Thrombectomy Using Machine Learning.

Background and Purpose- The clinical course of acute ischemic stroke with large vessel occlusion (LVO) is a multifactorial process with various progno...

An artificial intelligence-enabled ECG algorithm for the identification of patients with atrial fibrillation during sinus rhythm: a retrospective analysis of outcome prediction.

BACKGROUND: Atrial fibrillation is frequently asymptomatic and thus underdetected but is associated with stroke, heart failure, and death. Existing sc...

Multicenter experience with photoselective vaporization of the prostate on men taking novel oral anticoagulants.

OBJECTIVE: Photoselective vaporization of the prostate (PVP) is a widely performed surgical procedure for benign prostatic obstruction. This approach ...

On the interpretability of machine learning-based model for predicting hypertension.

BACKGROUND: Although complex machine learning models are commonly outperforming the traditional simple interpretable models, clinicians find it hard t...

Robot-assisted gait training for balance and lower extremity function in patients with infratentorial stroke: a single-blinded randomized controlled trial.

BACKGROUND: Balance impairments are common in patients with infratentorial stroke. Although robot-assisted gait training (RAGT) exerts positive effect...

The Current Research Landscape of the Application of Artificial Intelligence in Managing Cerebrovascular and Heart Diseases: A Bibliometric and Content Analysis.

The applications of artificial intelligence (AI) in aiding clinical decision-making and management of stroke and heart diseases have become increasing...

Robot-Assisted Arm Training in Chronic Stroke: Addition of Transition-to-Task Practice.

. Robot-assisted therapy provides high-intensity arm rehabilitation that can significantly reduce stroke-related upper extremity (UE) deficits. Motor ...

Validation of computerized square-drawing based evaluation of motor function in patients with stroke.

Human-administered clinical scales are commonly used for quantifying motor performance and determining the course of therapy in post-stroke individual...

Acute stroke rehabilitation for gait training with cyborg type robot Hybrid Assistive Limb: A pilot study.

Robot-assisted gait training following acute stroke could allow patients with severe disability to receive a high dosage and intensity of gait trainin...

Prediction of Aneurysm Stability Using a Machine Learning Model Based on PyRadiomics-Derived Morphological Features.

Background and Purpose- Discrimination of the stability of intracranial aneurysms is critical for determining the treatment strategy, especially in sm...

Automatic identification of atherosclerosis subjects in a heterogeneous MR brain imaging data set.

Carotid-artery atherosclerosis (CA) contributes significantly to overall morbidity and mortality in ischemic stroke. We propose a machine learning tec...

Collateral Automation for Triage in Stroke: Evaluating Automated Scoring of Collaterals in Acute Stroke on Computed Tomography Scans.

Computed tomography angiography (CTA) collateral scoring can identify patients most likely to benefit from mechanical thrombectomy and those more like...

Computer-Aided Diagnosis and Clinical Trials of Cardiovascular Diseases Based on Artificial Intelligence Technologies for Risk-Early Warning Model.

The use of artificial intelligence in medicine is currently an issue of great interest, especially with regard to the diagnostic or predictive analysi...