Strokes

A deep-learning approach to predict bleeding risk over time in patients on extended anticoagulation therapy.

BACKGROUND: Thus far, all the clinical models developed to predict major bleeding in patients on ext...

Socially Assistive Robot for Stroke Rehabilitation: A Long-Term in-the-Wild Pilot Randomized Controlled Trial.

Socially assistive robots (SARs) have been suggested as a platform for post-stroke training. It is n...

Differentiating ischemic stroke patients from healthy subjects using a large-scale, retrospective EEG database and machine learning methods.

OBJECTIVES: We set out to develop a machine learning model capable of distinguishing patients presen...

Text mining of hypertension researches in the west Asia region: a 12-year trend analysis.

More than half of the world population lives in Asia and hypertension (HTN) is the most prevalent ri...

On the relationship between various anticoagulants and robot-assisted radical prostatectomy: a single-surgeon serial analysis.

Prostate cancer patients often have other health conditions and take anticoagulants. It was believed...

Machine learning applied to gait analysis data in cerebral palsy and stroke: A systematic review.

BACKGROUND: Among neurological pathologies, cerebral palsy and stroke are the main contributors to w...

A Comprehensive Review: Robot-Assisted Treatments for Gait Rehabilitation in Stroke Patients.

Robot-assisted gait training (RAGT) is at the cutting edge of stroke rehabilitation, offering a grou...

Posterior circulation ischemic stroke: radiomics-based machine learning approach to identify onset time from magnetic resonance imaging.

PURPOSE: Posterior circulation ischemic stroke (PCIS) possesses unique features. However, previous s...

Impaired proprioception and magnified scaling of proprioceptive error responses in chronic stroke.

BACKGROUND: Previous work has shown that ~ 50-60% of individuals have impaired proprioception after ...

Unsupervised robot-assisted rehabilitation after stroke: feasibility, effect on therapy dose, and user experience.

BACKGROUND: Unsupervised robot-assisted rehabilitation is a promising approach to increase the dose ...

A Clinical and Imaging Fused Deep Learning Model Matches Expert Clinician Prediction of 90-Day Stroke Outcomes.

BACKGROUND AND PURPOSE: Predicting long-term clinical outcome in acute ischemic stroke is beneficial...

Discourse- and lesion-based aphasia quotient estimation using machine learning.

Discourse is a fundamentally important aspect of communication, and discourse production provides a ...

Predicting ischemic stroke patients' prognosis changes using machine learning in a nationwide stroke registry.

Accurately predicting the prognosis of ischemic stroke patients after discharge is crucial for physi...

Machine learning identifies novel coagulation genes as diagnostic and immunological biomarkers in ischemic stroke.

BACKGROUND: Coagulation system is currently known associated with the development of ischemic stroke...

Robot-assisted support combined with electrical stimulation for the lower extremity in stroke patients: a systematic review.

. The incidence of stroke rising, leading to an increased demand for rehabilitation services. Litera...

PRERISK: A Personalized, Artificial Intelligence-Based and Statistically-Based Stroke Recurrence Predictor for Recurrent Stroke.

BACKGROUND: Predicting stroke recurrence for individual patients is difficult, but individualized pr...

Evaluations of artificial intelligence and machine learning algorithms in neurodiagnostics.

This article evaluates the ethical implications of utilizing artificial intelligence (AI) algorithms...

Prediction of cardiovascular and renal risk among patients with apparent treatment-resistant hypertension in the United States using machine learning methods.

Apparent treatment-resistant hypertension (aTRH), defined as blood pressure (BP) that remains uncont...

Artificial intelligence to improve the diagnosis of pulmonary hypertension: promises and pitfalls.

Predicting hypertension control using machine learning.

Hypertension is a widely prevalent disease and uncontrolled hypertension predisposes affected indivi...

Diffusion-/perfusion-weighted imaging fusion to automatically identify stroke within 4.5 h.

OBJECTIVES: We aimed to develop machine learning (ML) models based on diffusion- and perfusion-weigh...