尿路感染的智能诊断:人工智能是快速解决方案吗?
Nithesh Naik1, Ali Talyshinskii2, Dasharathraj K Shetty3
1Department of Mechanical and Industrial Engineering, Manipal Institute of Technology, Manipal Academy of Higher Education, Manipal, 576104, Karnataka, India. nithesh.naik@manipal.edu.
Current urology reports
|December 19, 2023
概括
人工智能 (AI) 在支持尿路感染 (UTI) 诊断方面表现有前途. 然而,目前的人工智能研究需要更大,更多样化的数据集和外部验证才能获得可靠的临床应用.
科学领域:
- 医疗信息学 医疗信息学
- 医疗保健中的人工智能
- 诊断支持系统 诊断支持系统
背景情况:
- 人工智能 (AI) 有潜力提高医生在诊断尿路感染 (UTI) 的工作流程.
- 现有的评论往往有局限性,专注于狭窄的数据,特定的AI算法,或缺乏专门研究的全面分析.
- 需要进行专注的审查,以评估目前支持尿路感染诊断的AI系统的现状.
研究的目的:
- 进行小型审查,以确定基于AI的系统的当前状态,以支持尿路感染诊断.
主要方法:
- 关于人工智能在尿路感染诊断中的应用研究的文献综述.
- 分析报告的性能指标和现有人工智能模型的方法限制.
- 评估当前人工智能系统对临床整合的准备程度.
主要成果:
- 已有足够的出版物来了解AI在尿路感染诊断中的潜力,报告的表现指标通常是示例性的.
- 许多研究都存在缺陷:样本规模小,非异质,缺乏外部验证.
- 由于这些局限性,当前的AI模型尚未准备好作为尿路感染诊断的完整医生助理.
结论:
- 人工智能算法显示出对尿路感染诊断的潜力,但仍然存在重大局限性.
- 进一步的研究需要大型,异质,前性收集的数据集和外部验证.
- 探索性研究应优先考虑对未来临床工作流程价值评估的AI最佳实践的遵守.
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