Artificial intelligence in prostate cancer.

Journal: Chinese medical journal
Published Date: Jul 9, 2025

Abstract

Prostate cancer (PCa) ranks as the second most prevalent malignancy among men worldwide. Early diagnosis, personalized treatment, and prognosis prediction of PCa play a crucial role in improving patients' survival rates. The advancement of artificial intelligence (AI), particularly the utilization of deep learning (DL) algorithms, has brought about substantial progress in assisting the diagnosis, treatment, and prognosis prediction of PCa. The introduction of the foundation model has revolutionized the application of AI in medical treatment and facilitated its integration into clinical practice. This review emphasizes the clinical application of AI in PCa by discussing recent advancements from both pathological and imaging perspectives. Furthermore, it explores the current challenges faced by AI in clinical applications while also considering future developments, aiming to provide a valuable point of reference for the integration of AI and clinical applications.

Authors

  • Wei Li
    Department of Nephrology, The Second Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, China.
  • Ruoyu Hu
    Department of Urology, Renji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200127, China.
  • Quan Zhang
    Department of Pulmonary and Critical Care Medicine, The Second Xiangya Hospital, Central South University, Changsha, China.
  • Zhangsheng Yu
    Department of Bioinformatics and Biostatistics, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai, China.
  • Longxin Deng
    Department of Urology, Shanghai Changhai Hospital, Second Military Medical University, Shanghai 200433, China.
  • Xinhao Zhu
    Shanghai Jiao Tong University School of Medicine, Shanghai, China.
  • Yujia Xia
    Department of Bioinformatics and Biostatistics, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai, China.
  • Zijian Song
    Department of Urology, Renji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200127, China.
  • Alessia Cimadamore
    Section of Pathological Anatomy, Polytechnic University of the Marche Region, School of Medicine, United Hospitals, Ancona, Italy.
  • Fei Chen
    Department of Electrical and Electronic Engineering, Southern University of Science and Technology, Shenzhen, China.
  • Antonio Lopez-Beltran
    Department of Pathology and Surgery, Faculty of Medicine, Cordoba, Spain.
  • Rodolfo Montironi
    Section of Pathological Anatomy, Polytechnic University of the Marche Region, School of Medicine, United Hospitals, Ancona, Italy. Electronic address: r.montironi@univpm.it.
  • Liang Cheng
    College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, 150001, China. liangcheng@hrbmu.edu.cn.
  • Rui Chen
    College of Food Science and Engineering, Northwest A&F University, Yangling 712100, Shanxi, China.

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