How do deep-learning models generalize across populations? Cross-ethnicity generalization of COPD detection.

ABSTRACT:

Objectives

To evaluate the performance and potential biases of deep-learning models in detecting chronic obstructive pulmonary disease (COPD) on chest CT scans across different ethnic groups, specifically non-Hispanic White (NHW) and African American (AA) populations.

Materials and methods

Inspiratory chest CT and clinical data from 7549 Genetic epidemiology of COPD individuals (mean age 62 years old, 56-69 interquartile range), including 5240 NHW and 2309 AA individuals, were retrospectively analyzed. Several factors influencing COPD binary classification performance on different ethnic populations were examined: (1) effects of training population: NHW-only, AA-only, balanced set (half NHW, half AA) and the entire set (NHW + AA all); (2) learning strategy: three supervised

SUBMITTER: D Almeida S 

PROVIDER: S-EPMC11306482 | biostudies-literature | 2024 Aug

REPOSITORIES: biostudies-literature