Deep Learning Provides a New Magnetic Resonance Imaging-Based Prognostic Biomarker for Recurrence Prediction in High-Grade Serous Ovarian Cancer

Deep Learning Provides a New Magnetic Resonance Imaging-Based Prognostic Biomarker for Recurrence Prediction in High-Grade Serous Ovarian Cancer

This study aims to use a deep learning method to develop a signature extract from preoperative magnetic resonance imaging (MRI) and to evaluate its ability as a non-invasive recurrence risk prognostic marker in patients with advanced high-grade serous ovarian cancer (HGSOC). Our study comprises a to...

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Bibliographic Details
Main Authors: Lili Liu, Haoming Wan, Li Liu, Jie Wang, Yibo Tang, Shaoguo Cui, Yongmei Li
Format: Article
Language:English
Published: MDPI AG 2023-02-01
Series:Diagnostics
Subjects:
high-grade serous ovarian cancer
deep learning
magnetic resonance imaging
Online Access:https://www.mdpi.com/2075-4418/13/4/748

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https://www.mdpi.com/2075-4418/13/4/748

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