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. 2021 Jan 2;57(1):155–163. doi: 10.1002/uog.23530

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© 2020 The Authors. Ultrasound in Obstetrics & Gynecology published by John Wiley & Sons Ltd on behalf of International Society of Ultrasound in Obstetrics and Gynecology.

This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

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UOG-23530-FIG-0002-c — Receiver‐operating‐characteristics (ROC) curves for distinguishing between benign and malignant ovarian tumors of deep‐learning models VGG16 (), ResNet50 () and MobileNet () and ensemble of the three models (Ovry‐Dx1 in (a) and Ovry‐Dx2 in (b); ()), in all patients in test set (a) and when excluding inconclusive cases (predicted probability of malignancy between 0.4 and 0.6) (b). In (a), ROC curve of IOTA simple‐rules risk () and operating point for expert subjective assessment () are also shown.

Inline graphic — Receiver‐operating‐characteristics (ROC) curves for distinguishing between benign and malignant ovarian tumors of deep‐learning models VGG16 (), ResNet50 () and MobileNet () and ensemble of the three models (Ovry‐Dx1 in (a) and Ovry‐Dx2 in (b); ()), in all patients in test set (a) and when excluding inconclusive cases (predicted probability of malignancy between 0.4 and 0.6) (b). In (a), ROC curve of IOTA simple‐rules risk () and operating point for expert subjective assessment () are also shown.