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. 2022 Nov 23;12:895177. doi: 10.3389/fonc.2022.895177

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Copyright © 2022 Lei, Yu, Li, Yao, Wang, Gao, Wu, Ren, Tan, Zhang, Chen, Lin and Yao

This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

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Patients’ recruitment and study design. A total of 93 patients with preoperative magnetic resonance imaging from the Sun Yat-sen Memorial Hospital were enrolled. The two representative deep learning models (whole abdomen model and primary tumor model) were constructed and validated with the same training and validation cohorts, then compared for performance. EOC, epithelial ovarian cancer; CE-MRI, contrast-enhanced magnetic resonance imaging; IDS, interval debulking surgery; PDS, primary debulking surgery.