AIMC Topic: Stroke

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Machine learning for stroke in heart failure with reduced ejection fraction but without atrial fibrillation: A post-hoc analysis of the WARCEF trial.

European journal of clinical investigation
BACKGROUND: The prediction of ischaemic stroke in patients with heart failure with reduced ejection fraction (HFrEF) but without atrial fibrillation (AF) remains challenging. Our aim was to evaluate the performance of machine learning (ML) in identif...

Optimizing early diagnosis by integrating multiple classifiers for predicting brain stroke and critical diseases.

Scientific reports
Machine learning has gained attention in the medical field. Continuous efforts are being made to develop robust models for early prognosis purposes. The brain is the most pivotal organ in the human body. A brain stroke is generally caused by a blocka...

An interpretable machine learning scoring tool for estimating time to recurrence readmissions in stroke patients.

International journal of medical informatics
BACKGROUND: Stroke recurrence readmission poses an additional burden on both patients and healthcare systems. Risk stratification aims to accurately divide patients into groups to provide targeted interventions at reducing readmission. To accurately ...

Partial prior transfer learning based on self-attention CNN for EEG decoding in stroke patients.

Scientific reports
The utilization of motor imagery-based brain-computer interfaces (MI-BCI) has been shown to assist stroke patients activate motor regions in the brain. In particular, the brain regions activated by unilateral upper limb multi-task are more extensive,...

An ANN models cortical-subcortical interaction during post-stroke recovery of finger dexterity.

Journal of neural engineering
Finger dexterity, and finger individuation in particular, is crucial for human movement, and disruptions due to brain injury can significantly impact quality of life. Understanding the neurological mechanisms responsible for recovery is vital for eff...

Artificial intelligence and stroke imaging.

Current opinion in neurology
PURPOSE OF REVIEW: Though simple in its fundamental mechanism - a critical disruption of local blood supply - stroke is complicated by the intricate nature of the neural substrate, the neurovascular architecture, and their complex interactions in gen...

Predicting stroke severity of patients using interpretable machine learning algorithms.

European journal of medical research
BACKGROUND: Stroke is a significant global health concern, ranking as the second leading cause of death and placing a substantial financial burden on healthcare systems, particularly in low- and middle-income countries. Timely evaluation of stroke se...

Application of Isokinetic Dynamometry Data in Predicting Gait Deviation Index Using Machine Learning in Stroke Patients: A Cross-Sectional Study.

Sensors (Basel, Switzerland)
BACKGROUND: Three-dimensional gait analysis, supported by advanced sensor systems, is a crucial component in the rehabilitation assessment of post-stroke hemiplegic patients. However, the sensor data generated from such analyses are often complex and...

Generalizable self-supervised learning for brain CTA in acute stroke.

Computers in biology and medicine
Acute stroke management involves rapid and accurate interpretation of CTA imaging data. However, generalizable models for multiple acute stroke tasks able to learn from unlabeled data do not exist. We propose a linear probed self-supervised contrasti...

Impact of upper extremity robotic rehabilitation on respiratory parameters, functional capacity and dyspnea in patients with stroke: a randomized controlled study.

Neurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology
BACKGROUND: Stroke leads to reduced mobility and functional capacity, also negatively affects respiratory functions and muscle strength.