人工智能在泌尿系统肿瘤中的应用研究进展

doi:10.19401/j.cnki.1007-3639.2022.01.009

摘要/Abstract

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。

关键词: 人工智能, 机器学习, 泌尿系统肿瘤, 前列腺癌, 肾癌, 膀胱癌

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.

Key words: Artificial intelligence, Machine learning, Genitourinary cancers, Prostate cancer, Renal cancer, Bladder cancer

中图分类号:

R737.1

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. 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.

XU Wenhao, TIAN Xi, Aihetaimujiang·Anwaier , QU Yuanyuan, SHI Guohai, ZHANG Hailiang, YE Dingwei. A systematic review of current advancements of artificial intelligence in genitourinary cancers[J]. China Oncology, 2022, 32(1): 68-74.

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