Comparing traditional modeling approaches versus predictive analytics methods for predicting multiple sclerosis relapse-Reference-Cited by-同舟云学术

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Comparing traditional modeling approaches versus predictive analytics methods for predicting multiple sclerosis relapse

Published:2022-01 Issue: Volume:57 Page:103330
ISSN:2211-0348
Container-title:Multiple Sclerosis and Related Disorders
language:en
Short-container-title:Multiple Sclerosis and Related Disorders

Author:

Walsh K.,Shah R.,Armstrong J.K.,Moore E.S.,Oliver B.J.

Funder

Biogen Inc

Publisher

Elsevier BV

Subject

Neurology (clinical),Neurology,General Medicine

Reference20 articles.

1. The cost-effectiveness of disease-modifying therapies for the treatment of relapsing-remitting multiple sclerosis;Bozkaya;J. Med. Econ.,2017

2. Smote: synthetic minority over-sampling technique;Chawla;J. Artif. Intell. Res.,2002

3. The advantages of the Matthews correlation coefficient (MCC) over F1 score and accuracy in binary classification evaluation;Chicco;BMC Genomics,2020

4. Random forest versus logistic regression: a large-scale benchmark experiment;Couronne;BMC Bioinformatics,2018

5. National Multiple Sclerosis Society,2021

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