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...
| Main Authors: | , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Public Library of Science (PLoS)
2017-01-01
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| Series: | PLoS ONE |
| Online Access: | http://europepmc.org/articles/PMC5381810?pdf=render |