Pathological changes or technical artefacts? The problem of the heterogenous databases in COVID-19 CXR image analysis.

ABSTRACT:

Background

When the COVID-19 pandemic commenced in 2020, scientists assisted medical specialists with diagnostic algorithm development. One scientific research area related to COVID-19 diagnosis was medical imaging and its potential to support molecular tests. Unfortunately, several systems reported high accuracy in development but did not fare well in clinical application. The reason was poor generalization, a long-standing issue in AI development. Researchers found many causes of this issue and decided to refer to them as confounders, meaning a set of artefacts and methodological errors associated with the method. We aim to contribute to this steed by highlighting an undiscussed confounder related to image resolution.

Methods

20 216 chest X-ray images (CXR) from worldwide

SUBMITTER: Socha M 

PROVIDER: S-EPMC10278898 | biostudies-literature | 2023 Oct

REPOSITORIES: biostudies-literature