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. 2019 Mar 22;2(3):e191095. doi: 10.1001/jamanetworkopen.2019.1095

Figure 1. Results of External Validation Tests and Observer Performance Tests.

Figure 1.

The deep learning–based automatic detection algorithm (DLAD) showed consistently high image-wise classification (area under the receiver operating characteristic curve [AUROC], 0.973-1.000) (A) and lesion-wise localization (area under the alternative free-response receiver operating characteristic curve [AUAFROC], 0.923-0.985) (B) performances in external validation tests. In comparison of performance with physicians, the DLAD showed significantly high classification (AUROC, 0.983 vs 0.814-0.932) (C) and localization (AUAFROC, 0.985 vs 0.781-0.907) (D) performances than all observer groups.