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中华腔镜泌尿外科杂志(电子版) ›› 2024, Vol. 18 ›› Issue (06) : 541 -546. doi: 10.3877/cma.j.issn.1674-3253.2024.06.002

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人工智能应用于前列腺癌患者预后预测的研究现状及展望
李伟1,2, 宋子健1, 赖衍成3, 周睿4, 吴涵5, 邓龙昕3, 陈锐1,()   
  1. 1.200127 上海交通大学医学院附属仁济医院泌尿科
    2.200003 上海,海军军医大学(第二军医大学)第二附属医院全科基地
    3.510515 广州,南方医科大学第一临床医学院
    4.200127 上海交通大学医学院附属仁济医院病理科
    5.200433 上海 ,海军军医大学(第二军医大学)第一附属医院泌尿外科
  • 收稿日期:2024-08-26 出版日期:2024-12-01
  • 通信作者: 陈锐
  • 基金资助:
    国家自然科学基金项目(82272905)上海市自然科学基金面上项目(22ZR1478000)

The current state and prospects of artificial intelligence applied to prognosis prediction in prostate cancer patients

Wei Li1,2, Zijian Song1, Yancheng Lai3, Rui Zhou4, Han Wu5, Longxin Deng3, Rui Chen1,()   

  1. 1.Department of Urology,Renji Hospital,Shanghai Jiao Tong University School of Medicine,Shanghai 200127,China
    2.Department of General Practice,the Second Affiliated Hospital of Naval Medical University (Second Military Medical University),Shanghai 200003,China
    3.The First Clinical Medical School,Southern Medical University,Guangzhou 510515,China
    4.Department of Pathology,Renji Hospital,Shanghai Jiao Tong University School of Medicine,Shanghai 200127,China
    5.Department of Urology,The First Affiliated Hospital of Naval Medical University (Second Military Medical University),Shanghai 200433,China
  • Received:2024-08-26 Published:2024-12-01
  • Corresponding author: Rui Chen
引用本文:

李伟, 宋子健, 赖衍成, 周睿, 吴涵, 邓龙昕, 陈锐. 人工智能应用于前列腺癌患者预后预测的研究现状及展望[J]. 中华腔镜泌尿外科杂志(电子版), 2024, 18(06): 541-546.

Wei Li, Zijian Song, Yancheng Lai, Rui Zhou, Han Wu, Longxin Deng, Rui Chen. The current state and prospects of artificial intelligence applied to prognosis prediction in prostate cancer patients[J]. Chinese Journal of Endourology(Electronic Edition), 2024, 18(06): 541-546.

前列腺癌是男性最常见的恶性肿瘤之一,其发病率在全球范围内呈上升趋势。前列腺癌患者预后的准确判断是制定个体化治疗方案和长期管理的关键参考因素,但是目前缺乏客观、准确、统一的工具。近年来,人工智能技术在医疗领域的应用日益广泛,特别是在前列腺癌的预后预测方面展现出巨大的潜力,具有代表性的研究成果包括通过机器学习模型对多参数核磁共振中的影像特征进行识别,可实现对患者预后预测的准确率超过前列腺影像报告和数据系统;通过机器学习模型对病理切片进行识别,可实现对患者预后预测的准确率超过传统的Gleason评分系统。本文旨在阐述人工智能在前列腺癌预后预测的现状,讨论当前发展存在的问题,并展望未来的发展趋势。

Prostate cancer is one of the most common malignant tumors among men,and its incidence is on an upward trend worldwide. The accurate prognosis prediction of prostate cancer patients is a crucial reference for formulating personalized treatment plans and long-term management,but currently there is a lack of objective,accurate,and standardized tools. In recent years,the application of artificial intelligence technology in the medical field has become increasingly extensive,especially in the prognostic prediction of prostate cancer. It has shown tremendous potential.Representative research achievements include the identification of imaging features in multiparametric magnetic resonance through machine learning models,which can achieve an accuracy rate for patient prognosis prediction that exceeds the Prostate Imaging Reporting and Data System (PI-RADS). Additionally,through machine learning models,the identification of pathological sections can achieve an accuracy rate for patient prognosis prediction that surpasses the traditional Gleason scoring system. This article aims to review the current state of artificial intelligence in the prognostic prediction of prostate cancer,discuss the existing problems in its development,and look forward to future development trends.

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