对于冲击波石术的AI现状:YAU和EAU内分泌学的系统审查
Ali Talyshinskii1,2,3, Patrick Juliebø-Jones4,5, Lazaros Tzelves4,6,7
1Department of Urology and Andrology, Astana Medical University, Astana, Kazakhstan. urovator@gmail.com.
World journal of urology
|July 11, 2025
概括
人工智能 (AI) 在治疗结石方面表现有前途,使用体外冲击波石术 (ESWL) 来预测结果和手术内辅助. 为了临床整合,需要进行更多的多机构研究.
科学领域:
- 腎臟病學 (nephrology) 是一種醫學專業.
- 医疗信息学 医疗信息学
- 人工智能的人工智能
背景情况:
- 石病的治疗,特别是体外冲击波石 (ESWL),是技术进步的一个领域.
- 人工智能 (AI) 具有提高诊断准确性和治疗疗效的潜力.
研究的目的:
- 巩固人工智能在ESWL用于结石病的应用的证据.
- 评估将AI整合到ESWL管理的临床实践中的可行性.
主要方法:
- 在2025年3月,在主要数据库 (PubMed,Google Scholar,ACM,CINAHL,IEEE Xplore) 进行了系统的文献搜索.
- 包括专注于人工智能模型开发,验证和/或ESWL测试的研究,无论临床背景如何.
- 纳入标准要求以英语出版物.
主要成果:
- 17项研究符合纳入标准,分为预测结果 (14项研究) 和手术内辅助 (3项研究).
- 人工智能模型展示了有前途的结果,通常表现优于传统的统计方法.
- 在AI模型方法,输入参数 (例如,BMI) 和许多单中心研究中缺乏外部验证的显著异质性被注意到,影响了概括性.
结论:
- 人工智能在预测ESWL结果和提供手术内辅助方面显示出越来越大的潜力.
- 参数的标准化和通过前性,多机构研究的外部验证对于成功地将AI整合到ESWL管理中至关重要.
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