Machine learning in ovarian cancer: a bibliometric and visual analysis from 2004 to 2024.

Journal: Discover oncology
Published Date: May 13, 2025

Abstract

OBJECTIVE: Ovarian cancer (OC) is a common malignant tumor in women, with poor prognosis and high mortality rates. Early diagnosis, screening, and prognostic prediction of OC have long been focal points and challenges in this field. In recent years, machine learning (ML) has gradually demonstrated its unique advantages in the early diagnosis, screening, and prognostic prediction of tumors, including OC.This study aims to analyze global development trends and research hotspots in the application of ML for OC, thereby providing a reference for future research directions.

Authors

  • Xian Zeng
    The College of Biomedical Engineering and Instrument Science, Zhejiang University, 310027 Hangzhou, Zhejiang, China.
  • Zude Li
    Faculty of Public Administration, Guilin University of Technology, Guilin, China.
  • Lilin Dai
    Department of Pharmacy, Affiliated Hospital of Guilin Medical University, Guilin, China.
  • Jiang Li
  • Luqin Liao
    Department of Pharmacy, Affiliated Hospital of Guilin Medical University, Guilin, China. 42489289@qq.com.
  • Wei Chen
    Department of Urology, Zigong Fourth People's Hospital, Sichuan, China.

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