Exploration of machine learning techniques in predicting multiple sclerosis disease course
Abstract
To explore the value of machine learning methods for predicting multiple sclerosis disease course.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 build the classifier, and compared to logistic regression (LR) using demographic, clinical and MRI data obtained at years one and two to predict EDSS at five years...
Paper Details
Title
Exploration of machine learning techniques in predicting multiple sclerosis disease course
Published Date
Apr 5, 2017
Journal
Volume
12
Issue
4
Pages
e0174866 - e0174866
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