Considering patient clinical history impacts performance of machine learning models in predicting course of multiple sclerosis

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 Relap...

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Detalles Bibliográficos
Autores principales: Seccia, Ruggiero, Gammelli, Daniele, Dominici, Fabio, Romano, Silvia, Landi, Anna Chiara, Salvetti, Marco, Tacchella, Andrea, Zaccaria, Andrea, Crisanti, Andrea, Grassi, Francesca, Palagi, Laura
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2020
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7083323/
https://www.ncbi.nlm.nih.gov/pubmed/32196512
http://dx.doi.org/10.1371/journal.pone.0230219

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7083323/
https://www.ncbi.nlm.nih.gov/pubmed/32196512
http://dx.doi.org/10.1371/journal.pone.0230219

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