Unknown

Dataset Information

0

Preventing dataset shift from breaking machine-learning biomarkers.


ABSTRACT: Machine learning brings the hope of finding new biomarkers extracted from cohorts with rich biomedical measurements. A good biomarker is one that gives reliable detection of the corresponding condition. However, biomarkers are often extracted from a cohort that differs from the target population. Such a mismatch, known as a dataset shift, can undermine the application of the biomarker to new individuals. Dataset shifts are frequent in biomedical research, e.g.,  because of recruitment biases. When a dataset shift occurs, standard machine-learning techniques do not suffice to extract and validate biomarkers. This article provides an overview of when and how dataset shifts break machine-learning-extracted biomarkers, as well as detection and correction strategies.

SUBMITTER: Dockes J 

PROVIDER: S-EPMC8478611 | biostudies-literature |

REPOSITORIES: biostudies-literature

Similar Datasets

| S-EPMC6927796 | biostudies-literature
| S-EPMC8369168 | biostudies-literature
| S-EPMC7931945 | biostudies-literature
| S-EPMC4538374 | biostudies-literature
| S-EPMC8668825 | biostudies-literature
| S-EPMC6458448 | biostudies-literature
| S-EPMC6028898 | biostudies-other
| S-EPMC7303530 | biostudies-literature
| S-EPMC5516237 | biostudies-literature
| S-EPMC6908660 | biostudies-literature