尿病中的人工智能:利用和有效性的系统审查
Abdullah Altunhan1, Selim Soyturk1, Furkan Guldibi1
1Meram School of Medicine, Urology Department, Necmettin Erbakan University, Konya, Türkiye.
World journal of urology
|October 17, 2024
概括
人工智能 (AI) 在尿病管理方面表现出高精度,在石头检测,成分分析和预测石头通行方面表现出色. 与传统方法相比,人工智能模型显示出更高的准确性,这表明临床整合的潜力.
科学领域:
- 泌尿器科 泌尿器科 泌尿器科 泌尿器科
- 医疗信息学 医疗信息学
- 人工智能的人工智能
背景情况:
- 人工智能 (AI) 在医疗应用中正在迅速发展,在泌尿病学中具有显著的潜力,特别是对于尿病.
- 人工智能在石头疾病管理中为诊断,治疗和风险预测提供了有希望的功能.
研究的目的:
- 系统地审查和识别用于尿病研究的人工智能 (AI) 模型.
- 评估这些人工智能模型在各种泌尿病应用中的有效性和性能.
主要方法:
- 在主要数据库 (PubMed,EMBASE,Google Scholar,Cochrane Library) 中进行了系统的文献搜索.
- 关键词包括"泌尿病学"",人工智能"和"机器学习".
- 研究是根据PRISMA指南进行选择的,包括对尿病的原始AI研究,并排除非英语文章和评论.
主要成果:
- 在4851项已识别的研究中,包括了71项. 人工智能在石材成分分析 (88.2%) 和检测 (96.9%) 中实现了高精度.
- 人工智能在预测自发尿道结石通道 (87%) 和PCNL (82%) 和SWL (83%) 等治疗方式方面表现出很强的准确性.
- 人工智能模型通常在尿病中表现优于传统的诊断和治疗方法.
结论:
- 人工智能在尿病管理中发挥着越来越重要的作用,超过了传统的诊断,监测和治疗方法.
- 高精度和准确率表明AI已经准备好整合到常规的临床实践中.
- 需要进一步的研究来确认AI的长期实用性,并将其作为泌尿器科护理的标准工具.
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