Machine learning for brain stroke: a review

MS Sirsat, E Fermé, J Camara - Journal of Stroke and Cerebrovascular …, 2020 - Elsevier
Abstract Machine Learning (ML) delivers an accurate and quick prediction outcome and it
has become a powerful tool in health settings, offering personalized clinical care for stroke …

Machine learning in action: stroke diagnosis and outcome prediction

S Mainali, ME Darsie, KS Smetana - Frontiers in neurology, 2021 - frontiersin.org
The application of machine learning has rapidly evolved in medicine over the past decade.
In stroke, commercially available machine learning algorithms have already been …

Machine learning methods for functional recovery prediction and prognosis in post-stroke rehabilitation: a systematic review

S Campagnini, C Arienti, M Patrini, P Liuzzi… - Journal of …, 2022 - Springer
Background Rehabilitation medicine is facing a new development phase thanks to a recent
wave of rigorous clinical trials aimed at improving the scientific evidence of protocols. This …

Machine learning applications in stroke medicine: Advancements, challenges, and future prospectives

M Daidone, S Ferrantelli… - Neural Regeneration …, 2024 - journals.lww.com
Stroke is a leading cause of disability and mortality worldwide, necessitating the
development of advanced technologies to improve its diagnosis, treatment, and patient …

Cross-validation of predictive models for functional recovery after post-stroke rehabilitation

S Campagnini, P Liuzzi, A Mannini, B Basagni… - Journal of …, 2022 - Springer
Background Rehabilitation treatments and services are essential for the recovery of post-
stroke patients' functions; however, the increasing number of available therapies and the …

[HTML][HTML] Evaluation of Rehabilitation Outcomes in Patients with Chronic Neurological Health Conditions Using a Machine Learning Approach

G Santilli, M Mangone, F Agostini, M Paoloni… - Journal of Functional …, 2024 - mdpi.com
Background: Over one billion people worldwide suffer from neurological conditions that
cause mobility impairments, often persisting despite rehabilitation. Chronic neurological …

Predicting clinically significant motor function improvement after contemporary task-oriented interventions using machine learning approaches

HK Thakkar, W Liao, C Wu, YW Hsieh… - … of NeuroEngineering and …, 2020 - Springer
Background Accurate prediction of motor recovery after stroke is critical for treatment
decisions and planning. Machine learning has been proposed to be a promising technique …

[HTML][HTML] AI applications in adult stroke recovery and rehabilitation: a sco** review using AI

I Senadheera, P Hettiarachchi… - Sensors (Basel …, 2024 - pmc.ncbi.nlm.nih.gov
Stroke is a leading cause of long-term disability worldwide. With the advancements in
sensor technologies and data availability, artificial intelligence (AI) holds the promise of …

Machine learning analysis to predict the need for ankle foot orthosis in patients with stroke

YJ Choo, JK Kim, JH Kim, MC Chang, D Park - Scientific Reports, 2021 - nature.com
We investigated the potential of machine learning techniques, at an early stage after stroke,
to predict the need for ankle–foot orthosis (AFO) in stroke patients. We retrospectively …

Machine learning predicts clinically significant health related quality of life improvement after sensorimotor rehabilitation interventions in chronic stroke

WW Liao, YW Hsieh, TH Lee, C Chen, C Wu - Scientific Reports, 2022 - nature.com
Health related quality of life (HRQOL) reflects individuals perceived of wellness in health
domains and is often deteriorated after stroke. Precise prediction of HRQOL changes after …