Advances in artificial intelligence for the diagnosis and treatment of ovarian cancer (Review).

Journal: Oncology reports
Published Date:

Abstract

Artificial intelligence (AI) has emerged as a crucial technique for extracting high‑throughput information from various sources, including medical images, pathological images, and genomics, transcriptomics, proteomics and metabolomics data. AI has been widely used in the field of diagnosis, for the differentiation of benign and malignant ovarian cancer (OC), and for prognostic assessment, with favorable results. Notably, AI‑based radiomics has proven to be a non‑invasive, convenient and economical approach, making it an essential asset in a gynecological setting. The present study reviews the application of AI in the diagnosis, differentiation and prognostic assessment of OC. It is suggested that AI‑based multi‑omics studies have the potential to improve the diagnostic and prognostic predictive ability in patients with OC, thereby facilitating the realization of precision medicine.

Authors

  • Yanli Wang
    Department of Electrical Engineering and Computer Science, University of Missouri, Columbia, MO, USA.
  • Weihong Lin
    Department of Obstetrics and Gynecology, The Second Affiliated Hospital of Fujian Medical University, Quanzhou, Fujian 362000, P.R. China.
  • Xiaoling Zhuang
    Department of Pathology, The Second Affiliated Hospital of Fujian Medical University, Quanzhou, Fujian 362000, P.R. China.
  • Xiali Wang
    Department of Clinical Medicine, Quanzhou Medical College, Quanzhou, Fujian 362000, P.R. China.
  • Yifang He
    Department of Ultrasound, The Second Affiliated Hospital of Fujian Medical University, Quanzhou, Fujian 362000, P.R. China.
  • Luhong Li
    Department of Obstetrics and Gynecology, The Second Affiliated Hospital of Fujian Medical University, Quanzhou, Fujian 362000, P.R. China.
  • Guorong Lyu
    Department of Ultrasound, The Second Affiliated Hospital of Fujian Medical University, Quanzhou 362000, China.