机器学习（ML）和人工智能（AI）已展示出提高放射治疗患者护理的潜力。在此，我们回顾了适用于膀胱癌护理的最新进展，着眼于可能建议临床实施的研究。算法已被应用于临床记录、病理学和放射学数据，以生成准确的预测模型，用于预后和临床结果。AI也已显示出越来越多的用途，用于自动轮廓和有效创建涉及多个治疗计划的工作流程。随着技术逐步朝向膀胱癌患者的例行临床使用发展，我们还讨论了提高算法可解释性和可靠性的新兴方法。版权所有© 2022 Elsevier Inc.。保留所有权利。

Machine learning (ML) and artificial intelligence (AI) have demonstrated potential to improve the care of radiation oncology patients. Here we review recent advances applicable to the care of bladder cancer, with an eye towards studies that may suggest next steps in clinical implementation. Algorithms have been applied to clinical records, pathology, and radiology data to generate accurate predictive models for prognosis and clinical outcomes. AI has also shown increasing utility for auto-contouring and efficient creation of workflows involving multiple treatment plans. As technologies progress towards routine clinical use for bladder cancer patients, we also discuss emerging methods to improve interpretability and reliability of algorithms.Copyright © 2022 Elsevier Inc. All rights reserved.