Random forest-based model for the recurrence prediction of borderline ovarian tumor: clinical development and validation

Abstract Purpose This study aims to develop an effective machine learning (ML)-based predictive model for the recurrence of borderline ovarian tumor (BOT), and provide the guidelines of accurate clinical diagnosis and precise treatment for patients. Method A total of 660 patients diagnosed with BOT...

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主要な著者:	Liheng Yan, Qiulin Ye, Baole Shi, Juanjuan Liu, Yuexin Hu, Ouxuan Liu, Xiao Li, Bei Lin, Yue Qi
フォーマット:	Artigo
言語:	Inglês
出版事項:	Springer 2025-05-01
シリーズ:	Journal of Cancer Research and Clinical Oncology
主題:	Borderline ovarian tumor Recurrence prediction Machine learning Random forest Predictive modeling Fertility-sparing surgery
オンライン･アクセス:	https://doi.org/10.1007/s00432-025-06221-x
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