Decision tree model for predicting ovarian tumor malignancy based on clinical markers and preoperative circulating blood cells.

ABSTRACT:

Objective

Ovarian cancer is a serious malignant tumor threatening women's health. The early diagnosis and effective treatments of ovarian cancer remain inadequate, and about 70% of ovarian cancers are in advanced stages when discovered. This study aimed to use the decision tree method of artificial intelligence machine learning to build a model for predicting the benign and malignant degree of ovarian cancer patients.

Study design

A total of 758 patients were included in the study. These patients were diagnosed by B-ultrasound, CT or MR. The clinicopathological features and circulating blood cell indexes were recorded and analyzed. The prediction model of benign and malignant ovarian tumors was constructed by CART decision tree, and the receiver operating characteristic (ROC

SUBMITTER: Li Y 

PROVIDER: S-EPMC11844102 | biostudies-literature | 2025 Feb

REPOSITORIES: biostudies-literature