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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Detalles Bibliográficos
Autores principales: Liu, Lili, Wan, Haoming, Liu, Li, Wang, Jie, Tang, Yibo, Cui, Shaoguo, Li, Yongmei
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9954966/
https://www.ncbi.nlm.nih.gov/pubmed/36832236
http://dx.doi.org/10.3390/diagnostics13040748

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9954966/
https://www.ncbi.nlm.nih.gov/pubmed/36832236
http://dx.doi.org/10.3390/diagnostics13040748

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