人工智能算法在基于超声波的结石检测,分类,预测和管理中的应用:系统性审查
Mohammadreza Elhaie1, Abolfazl Koozari2, Salman Mohammed Albeshan3
1Isfahan University of Medical Sciences, Isfahan, Iran, Islamic Republic of. mrelhaie@gmail.com.
Abdominal radiology (New York)
|March 9, 2026
概括
人工智能 (AI) 和深度学习 (DL) 增强了对结石的超声波 (US),在检测和预测方面显示出高精度. 为了获得广泛的临床采用,需要进一步验证.
科学领域:
- 泌尿器科 泌尿器科 泌尿器科 泌尿器科
- 医疗成像医学成像
- 人工智能的人工智能
背景情况:
- 结石是一种常见的泌尿器科问题,通常通过超声波 (美国) 诊断,这有局限性.
- 人工智能 (AI) 和深度学习 (DL) 显示出改善美国结石管理的潜力.
研究的目的:
- 系统地审查美国的AI和DL应用程序,用于结石检测,分类,并发症预测和程序指导.
主要方法:
- 按照PRISMA指南进行系统审查,搜索多个数据库.
- 包括原始研究评估AI/DL在美国的结石与参考标准.
- 通过使用带有AI扩展的QUADAS-2评估研究质量.
主要成果:
- 包括9项研究,重点关注DL用于图像分析,预测建模和程序指导.
- 人工智能/DL模型表现出高性能,精度高达96.54%,AUC>0.90.
- 发现了方法异质性和有限的验证,限制了元分析.
结论:
- 人工智能和DL算法在美国对结石管理具有很高的准确性和实用性.
- 在各种应用中性能很高,解决了美国传统的局限性.
- 标准化验证和多式联运集成对于更广泛的采用至关重要.
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