When to and when not to use machine learning in risk prediction models
Abstract
Machine learning for health data science, fuelled by proliferation of data and reduced computational costs, has garnered considerable interest among researchers. The debate around the use of machine learning or classical medical statistics for medical research is long standing.1,2 Given major methodological advances and increased policy attention, renewed consideration is warranted for when machine learning should and should not be used in risk prediction models. In this Comment, we offer practical guidance on when (and when not) to use machine learning for risk prediction.
Fields of Study & Subjects
Explainable Artificial Intelligence (XAI)
Artificial Intelligence in Healthcare and Education
Statistical Methods and Inference
Publication details
- Journal / source
- The Lancet Digital Health
- Publisher
- Elsevier BV
- Volume
- 8
- Issue
- 2
- Pages
- 100954–100954
- Publication date
- 1 February 2026
- Language
- EN