Predicting disease activity in patients with multiple sclerosis: An explainable machine‐learning approach in the Mavenclad trials
Abstract 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 orienta...
Tallennettuna:
| Päätekijät: | , , , , , |
|---|---|
| Aineistotyyppi: | Artigo |
| Kieli: | Inglês |
| Julkaistu: |
Wiley
2022-07-01
|
| Sarja: | CPT: Pharmacometrics & Systems Pharmacology |
| Linkit: | https://doi.org/10.1002/psp4.12796 |
| Tagit: |
Ei tageja, Lisää ensimmäinen tagi!
|