Open AccessArtificial Intelligence Based on Blood Biomarkers Including CTCs Predicts Outcomes in Epithelial Ovarian Cancer: A Prospective Study
Author(s) -
Jun Ma,
Jiani Yang,
Yue Jin,
Shanshan Cheng,
Shan Huang,
Nan Zhang,
Yu Wang
Publication year - 2021
Publication title -
oncotargets and therapy
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.054
H-Index - 60
ISSN - 1178-6930
DOI - 10.2147/ott.s307546
Subject(s) - machine learning , random forest , circulating tumor cell , receiver operating characteristic , artificial intelligence , naive bayes classifier , medicine , oncology , logistic regression , proportional hazards model , ovarian cancer , support vector machine , cancer , computer science , metastasis
We aimed to develop an ovarian cancer-specific predictive framework for clinical use platinum-sensitivity and prognosis using machine learning methods based on multiple biomarkers, including circulating tumor cells (CTCs).