Artificial intelligence in prostate cancer: Definitions, current research, and future directions.

Journal: Urologic oncology
Published Date: Apr 13, 2022

Abstract

Multiple novel modalities tasking artificial intelligence based computational pathology applications and integrating other variables, such as risk factors, tumor microenvironment, genomic testing data, laboratory findings, clinical history, and radiology findings, will improve diagnostic consistency and generate a synergistic diagnostic workflow. In this article, we present the concise and contemporary review on the utilization of artificial intelligence in prostate cancer and identify areas for possible future applications.

Authors

  • Rose S George
    Department of Pathology and Laboratory Medicine, Albany Medical Center, Albany, NY.
  • Arkar Htoo
    Department of Pathology and Laboratory Medicine, Albany Medical Center, Albany, NY.
  • Michael Cheng
    Department of Medicine, Indianapolis, Indianapolis, IN.
  • Timothy M Masterson
    Department of Urology, Indianapolis, IN.
  • Kun Huang
    Department of Biomedical Informatics, The Ohio State University, Columbus, OH, 43210, USA. Kun.Huang@osumc.edu.
  • Nabil Adra
    Department of Medicine, Indianapolis, Indianapolis, IN; Department of Urology, Indianapolis, IN.
  • Hristos Z Kaimakliotis
    Department of Urology, Indianapolis, IN.
  • Mahmut Akgul
    Department of Pathology and Laboratory Medicine, Albany Medical Center, Albany, NY. Electronic address: akgulm@amc.edu.
  • Liang Cheng
    College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, 150001, China. liangcheng@hrbmu.edu.cn.

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