Logistic regression has similar performance to optimised machine learning algorithms in a clinical setting: application to the discrimination between type 1 and type 2 diabetes in young adults

Logistic regression has similar performance to optimised machine learning algorithms in a clinical setting: application to the discrimination between type 1 and type 2 diabetes in young adults

Abstract Background There is much interest in the use of prognostic and diagnostic prediction models in all areas of clinical medicine. The use of machine learning to improve prognostic and diagnostic accuracy in this area has been increasing at the expense of classic statistical models. Previous st...

Full description

Bibliographic Details
Main Authors: Anita L. Lynam, John M. Dennis, Katharine R. Owen, Richard A. Oram, Angus G. Jones, Beverley M. Shields, Lauric A. Ferrat
Format: Article
Language:English
Published: BMC 2020-06-01
Series:Diagnostic and Prognostic Research
Subjects:
Machine learning
Logistic regression
Model selection
Online Access:http://link.springer.com/article/10.1186/s41512-020-00075-2

Internet

http://link.springer.com/article/10.1186/s41512-020-00075-2

Similar Items