AI-Derived Blood Biomarkers for Ovarian Cancer Diagnosis: Systematic Review and Meta-Analysis.

Journal: Journal of medical Internet research
PMID:

Abstract

BACKGROUND: Emerging evidence underscores the potential application of artificial intelligence (AI) in discovering noninvasive blood biomarkers. However, the diagnostic value of AI-derived blood biomarkers for ovarian cancer (OC) remains inconsistent.

Authors

  • He-Li Xu
    Department of Clinical Epidemiology, Shengjing Hospital of China Medical University, Shenyang, China.
  • Xiao-Ying Li
    Department of Clinical Epidemiology, Shengjing Hospital of China Medical University, ShenYang, China.
  • Ming-Qian Jia
    Department of Clinical Epidemiology, Shengjing Hospital of China Medical University, ShenYang, China.
  • Qi-Peng Ma
    Department of Obstetrics and Gynecology, Shengjing Hospital of China Medical University, ShenYang, China.
  • Ying-Hua Zhang
    Department of Food Science, Northeast Agricultural University Harbin 150030 PR China.
  • Fang-Hua Liu
    Department of Clinical Epidemiology, Shengjing Hospital of China Medical University, ShenYang, China.
  • Ying Qin
    School of Economics and Management, Wuhan University, Bayi Road No.299, Wuchang District, Wuhan, 430072, China. qy1119@163.com.
  • Yu-Han Chen
    Department of Epidemiology, School of Public Health, China Medical University, ShenYang, China.
  • Yu Li
    Department of Public Health, Shihezi University School of Medicine, 832000, China.
  • Xi-Yang Chen
    Department of Clinical Epidemiology, Shengjing Hospital of China Medical University, ShenYang, China.
  • Yi-Lin Xu
    Department of Clinical Epidemiology, Shengjing Hospital of China Medical University, ShenYang, China.
  • Dong-Run Li
    Department of Clinical Epidemiology, Shengjing Hospital of China Medical University, ShenYang, China.
  • Dong-Dong Wang
    Jiangsu Key Laboratory of New Drug Research and Clinical Pharmacy and School of Pharmacy, Xuzhou Medical University, Xuzhou, 221004, Jiangsu, China. 13852029591@163.com.
  • Dong-Hui Huang
    Department of Clinical Epidemiology, Shengjing Hospital of China Medical University, ShenYang, China.
  • Qian Xiao
    International Initiative on Spatial Lifecourse Epidemiology (ISLE), the Netherlands; Department of Health and Human Physiology, University of Iowa, Iowa City, IA, 52242, USA; Department of Epidemiology, University of Iowa, Iowa City, IA, 52242, USA.
  • Yu-Hong Zhao
    Department of Clinical Epidemiology, Clinical Research Center, Shengjing Hospital, China Medical University, Shenyang, 110004, China. zhaoyuhong@sj-hospital.org.
  • Song Gao
    Department of Radiology, The Affiliated Hospital of Qingdao University, Qingdao, China.
  • Xue Qin
    Center for Genomic and Personalized Medicine, Guangxi Medical University, Nanning, Guangxi, China.
  • Tao Tao
    Huangshi Public Security Bureau, Huangshi 435000, China.
  • Ting-Ting Gong
    Department of Obstetrics and Gynecology, Shengjing Hospital of China Medical University, Shenyang, China. Electronic address: gongtt@sj-hospital.org.
  • Qi-Jun Wu
    Department of Obstetrics and Gynecology, Shengjing Hospital of China Medical University, Shenyang, China; Department of Clinical Epidemiology, Shengjing Hospital of China Medical University, Shenyang, China; Key Laboratory of Reproductive and Genetic Medicine (China Medical University), National Health Commission, Shenyang, China. Electronic address: wuqj@sj-hospital.org.