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

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

Abstract 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 phenomenon, combined with new trends in personalised medical therapies, is expected to change clinical pract...

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Bibliographic Details
Main Authors: Silvia Campagnini, Chiara Arienti, Michele Patrini, Piergiuseppe Liuzzi, Andrea Mannini, Maria Chiara Carrozza
Format: Article
Language:English
Published: BMC 2022-06-01
Series:Journal of NeuroEngineering and Rehabilitation
Subjects:
Automated pattern recognition
Clinical
Efficacy treatment
Machine learning
Prognosis
Regression analysis
Online Access:https://doi.org/10.1186/s12984-022-01032-4

Internet

https://doi.org/10.1186/s12984-022-01032-4

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