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

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

Abstract 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 for outcome prediction because of its high accuracy and ability to process large volumes of data. It has been used t...

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Bibliographic Details
Main Authors: Hiren Kumar Thakkar, Wan-wen Liao, Ching-yi Wu, Yu-Wei Hsieh, Tsong-Hai Lee
Format: Article
Language:English
Published: BMC 2020-09-01
Series:Journal of NeuroEngineering and Rehabilitation
Subjects:
Machine learning
Prognosis
Rehabilitation
Stroke
Motor function
Online Access:http://link.springer.com/article/10.1186/s12984-020-00758-3

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http://link.springer.com/article/10.1186/s12984-020-00758-3

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