Considering patient clinical history impacts performance of machine learning models in predicting co...
Considering patient clinical history impacts performance of machine learning models in predicting course of multiple sclerosis
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Publisher
United States: Public Library of Science
Journal title
Language
English
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Publisher
United States: Public Library of Science
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Scope and Contents
Contents
Multiple Sclerosis (MS) progresses at an unpredictable rate, but predictions on the disease course in each patient would be extremely useful to tailor therapy to the individual needs. We explore different machine learning (ML) approaches to predict whether a patient will shift from the initial Relapsing-Remitting (RR) to the Secondary Progressive (...
Alternative Titles
Full title
Considering patient clinical history impacts performance of machine learning models in predicting course of multiple sclerosis
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TN_cdi_plos_journals_2380031673
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_plos_journals_2380031673
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ISSN
1932-6203
E-ISSN
1932-6203
DOI
10.1371/journal.pone.0230219
