Exploration of machine learning techniques in predicting multiple sclerosis disease course.

Exploration of machine learning techniques in predicting multiple sclerosis disease course.

OBJECTIVE:To explore the value of machine learning methods for predicting multiple sclerosis disease course. METHODS:1693 CLIMB study patients were classified as increased EDSS≥1.5 (worsening) or not (non-worsening) at up to five years after baseline visit. Support vector machines (SVM) were used to...

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Bibliographic Details
Main Authors: Yijun Zhao, Brian C Healy, Dalia Rotstein, Charles R G Guttmann, Rohit Bakshi, Howard L Weiner, Carla E Brodley, Tanuja Chitnis
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2017-01-01
Series:PLoS ONE
Online Access:http://europepmc.org/articles/PMC5381810?pdf=render

Internet

http://europepmc.org/articles/PMC5381810?pdf=render

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