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Integrating additional factors into the International Federation of Gynecology and Obstetrics (FIGO) staging system is needed for accurate patient classification and survival prediction. In this study, we tested machine learning… Click to show full abstract
Integrating additional factors into the International Federation of Gynecology and Obstetrics (FIGO) staging system is needed for accurate patient classification and survival prediction. In this study, we tested machine learning as a novel tool for incorporating additional prognostic parameters into the conventional FIGO staging system for stratifying patients with epithelial ovarian carcinomas and evaluating their survival.
Keywords:
epithelial ovarian;
machine learning;
system;
ovarian carcinomas
Journal Title: Acta Obstetricia et Gynecologica Scandinavica
Year Published: 2021
Link to full text (if available)
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Journal Title: Acta Obstetricia et Gynecologica Scandinavica
Year Published: 2021
Link to full text (if available)
Share on Social Media: Sign Up to like & get
recommendations!