A Unified Framework on Generalizability of Clinical Prediction Models
To be useful, clinical prediction models (CPMs) must be generalizable to patients in new settings. Evaluating generalizability of CPMs helps identify spurious relationships in data, provides insights on when they fail, and thus, improves the explainability of the CPMs. There are discontinuities in c...
Main Authors: | , , |
---|---|
Format: | Article |
Language: | English |
Published: |
Frontiers Media S.A.
2022-04-01
|
Series: | Frontiers in Artificial Intelligence |
Subjects: | |
Online Access: | https://www.frontiersin.org/articles/10.3389/frai.2022.872720/full |