人工智能在泌尿系统肿瘤中的应用研究进展

徐文浩; 田熙; 艾合太木江·; 安外尔; 瞿元元; 施国海; 张海梁; 叶定伟

doi:10.19401/j.cnki.1007-3639.2022.01.009

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人工智能在泌尿系统肿瘤中的应用研究进展

综述 | 更新时间：2025-12-31

- 人工智能在泌尿系统肿瘤中的应用研究进展
- A systematic review of current advancements of artificial intelligence in genitourinary cancers
- 中国癌症杂志 2022年32卷第1期页码：68-74
- 作者机构：
  
  复旦大学附属肿瘤医院泌尿外科,复旦大学上海医学院肿瘤学系,上海 200032
- 作者简介：
  
  叶定伟 E-mail: dwyelie@163.com
- 基金信息：
- DOI：10.19401/j.cnki.1007-3639.2022.01.009
  中图分类号： R737.1
- 收稿：2021-07-07，
  
  修回：2021-09-23，
  
  纸质出版：2022-01-30
- 稿件说明：
移动端阅览
徐文浩, 田熙, 艾合太木江·, 等. 人工智能在泌尿系统肿瘤中的应用研究进展[J]. 中国癌症杂志, 2022,32(1):68-74.

Wenhao XU, Xi TIAN, Aihetaimujiang·, et al. A systematic review of current advancements of artificial intelligence in genitourinary cancers[J]. China Oncology, 2022, 32(1): 68-74.
徐文浩, 田熙, 艾合太木江·, 等. 人工智能在泌尿系统肿瘤中的应用研究进展[J]. 中国癌症杂志, 2022,32(1):68-74. DOI： 10.19401/j.cnki.1007-3639.2022.01.009.

Wenhao XU, Xi TIAN, Aihetaimujiang·, et al. A systematic review of current advancements of artificial intelligence in genitourinary cancers[J]. China Oncology, 2022, 32(1): 68-74. DOI： 10.19401/j.cnki.1007-3639.2022.01.009.

摘要

近年来

机器学习和神经网络技术的进步使得人工智能（artificial intelligence

AI）在指导临床诊断、治疗和资源投入等方面产生了巨大影响。在泌尿系统肿瘤领域

AI在改善前列腺癌、肾癌和膀胱癌的诊断和治疗方面取得了诸多进步

已可利用机器学习和神经网络技术自动化进行预后预测、治疗计划优化和患者随访教育等。有证据表明

AI指导可以显著降低泌尿系统肿瘤的诊断和治疗管理的主观性。尽管AI在泌尿系统肿瘤中的应用已经成为现代科技的热点

但对比真实世界的医疗决策时

AI仍然存在明显的局限性。通过对AI目前的优势和不足进行概述

旨在为未来AI在泌尿系统肿瘤的精准化、个性化诊治和长期管理中的应用提供参考。

Abstract

Recently

advances in machine learning and neural network technology have allowed artificial intelligence (AI) to further promote guidance of clinical diagnosis

treatment and resource expenditures. In genitourinary cancers

AI has made huge progress in improving the diagnosis and treatment of prostate

kidney and bladder cancers. Numerous studies have developed methods to utilize neural networks to automate prognostic prediction

treatment plan optimization and patient follow-up education. Obviously

AI guidance could markedly reduce the subjectivity of diagnosis and treatment management of genitourinary cancers. However

although the application of AI in cancer treatment has become a research hotspot in modern technology

there still exist obvious limitations of AI management when compared with real-world clinical strategies. Therefore

this article summarized the current advantages and disadvantages of AI to provide novel insights for the future application of AI in the precision

personalized diagnosis and treatment

and long-term management of both patients and urologists.

关键词

Keywords

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