Application of artificial intelligence in the diagnosis and prognostic prediction of ovarian cancer.

Journal: Computers in biology and medicine
Published Date: May 13, 2022

Abstract

In recent years, the wide application of artificial intelligence (AI) has dramatically improved the work efficiency of clinicians and reduced their workload. This review provides a glance at the latest advances in AI-assisted diagnosis and prognostic prediction of ovarian cancer (OC). We performed an advanced search in PubMed and IEEE/IET Electronic Library, and included 39 articles in this review. A comprehensive and objective criterion was built to assess the reliability and quality of all studies from four aspects: the size of datasets for model development, research design, the division of training sets and test sets, and the type of quantitative performance indicators. This review analyzed the construction of AI models, including data pre-processing methods, feature selection techniques, AI classifiers, or algorithms. Additionally, we compared the performance of these models built on different datasets, which may support researchers for further iteration and development of AI. Finally, we discussed the challenges and future directions for AI application in medicine.

Authors

  • Jingyang Zhou
    Queen Mary School, Medical Department, Nanchang University, Nanchang, 330031, Jiangxi Province, PR China.
  • Weiwei Cao
    School of Biomedical Engineering (Suzhou), University of Science and Technology of China, Division of Life Sciences and Medicine, Hefei, 230026, Anhui, China.
  • Lan Wang
    The Center of Psychosomatic Medicine, Sichuan Provincial Center for Mental Health, Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Chengdu 611731, China.
  • Zezheng Pan
    Faculty of Basic Medical Science, Nanchang University, Nanchang, 330006, Jiangxi Province, PR China.
  • Ying Fu
    Department of Ultrasound, Peking University Third Hospital, Beijing, China.

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