Extended Data Fig. 1: Analyzing underdiagnoses over subgroups of sex, age, within ALL dataset (combined CXR, CXP and NIH dataset on shared labels). | Nature Medicine

Extended Data Fig. 1: Analyzing underdiagnoses over subgroups of sex, age, within ALL dataset (combined CXR, CXP and NIH dataset on shared labels).

From: Underdiagnosis bias of artificial intelligence algorithms applied to chest radiographs in under-served patient populations

Extended Data Fig. 1

Fig. S1. Analyzing underdiagnoses over subgroups of sex, age, within ALL dataset (combined CXR, CXP and NIH dataset on shared labels). The results are averaged over 5 trained model with different random seed ± 95% confidence interval (CI). A. The underdiagnosis rate (measured by ‘No Finding’ FPR). B. The overdiagnosis rate (‘No Finding’ False Negative Rate (FNR)) over subgroups of sex, age. C. The intersectional underdiagnosis rates within only female patients. D. Examining the overdiagnosis rate for the intersectional identities. The number of images with actual 0 or 1 ‘No Finding’ label in the age - sex intersections in the test dataset is presented in Supplementary Table 1.

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