Predicting disease activity in patients with multiple sclerosis: An explainable machine‐learning approach in the Mavenclad trials

Multiple sclerosis (MS) is among the most common autoimmune disabling neurological conditions of young adults and affects more than 2.3 million people worldwide. Predicting future disease activity in patients with MS based on their pathophysiology and current treatment is pivotal to orientate future...

Descripción completa

Detalles Bibliográficos
Autores principales: Basu, Sreetama, Munafo, Alain, Ben‐Amor, Ali‐Frederic, Roy, Sanjeev, Girard, Pascal, Terranova, Nadia
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2022
Materias:
Research
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9286719/
https://www.ncbi.nlm.nih.gov/pubmed/35521742
http://dx.doi.org/10.1002/psp4.12796

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9286719/
https://www.ncbi.nlm.nih.gov/pubmed/35521742
http://dx.doi.org/10.1002/psp4.12796

Ejemplares similares