Accuracy of machine learning in the preoperative identification of ovarian borderline tumors: a meta-analysis.

Journal: Clinical radiology
Published Date:

Abstract

AIM: The objective of this study is to explore the diagnostic value of machine learning (ML) in borderline ovarian tumors through meta-analysis.

Authors

  • L Qi
    Department of Gynecology and Obstetrics, Yantai Yuhuangding Hospital Affiliated to Qingdao University, Yantai City, Shandong Province, China.
  • X Li
    1 School of Public Health, Capital Medical University, Beijing, China.
  • Y Yang
    Department of Forensic Medicine, Inner Mongolia Medical University, Hohhot 010030, China.
  • M Zhao
    State Key Laboratory of Ocean Engineering, School of Naval Architecture, Ocean and Civil Engineering, Shanghai Jiao Tong University, Shanghai, China.
  • A Lin
    Department of Neurological Surgery, Brain and Spinal Injury Center (BASIC), University of California, San Francisco, CA, USA.
  • L Ma
    Center for Laboratory Diagnosis, Yantai Yuhuangding Hospital Affiliated to Qingdao University, Yantai City, Shandong Province, China. Electronic address: yhdmali@163.com.