人工智能和机器学习对于免疫的先天性错误:当前状态和未来的承诺
Alexandra K Martinson1, Aaron T Chin2, Manish J Butte2
1Department of Pediatrics, Children's National Hospital, Washington, DC.
The journal of allergy and clinical immunology. In practice
|August 10, 2024
概括
人工智能 (AI) 和机器学习 (ML) 可以显著改善先天免疫错误 (IEI) 的早期诊断. 本综述审查了AI/ML在IEI识别和管理中的应用,以改善患者护理.
科学领域:
- 医疗信息学 医疗信息学
- 免疫学 免疫学 免疫学
- 机器学习 机器学习
背景情况:
- 人工智能 (AI) 和机器学习 (ML) 越来越多地用于医学.
- 人工智能/ML显示出改善临床实践和患者治疗结果的前景.
- 最近的进展集中在应用AI/ML来识别免疫的先天性错误 (IEI).
研究的目的:
- 为IEI领域的AI/ML应用提供全面的审查.
- 涵盖AI/ML使用的整个范围,从数据预处理到临床实施.
- 解决使用AI/ML用于IEI诊断和管理的挑战.
主要方法:
- 对医学和免疫学中AI/ML现有文献的审查.
- 对用于IEI识别电子健康记录数据的AI/ML算法的分析.
- 检查开发和实施临床决策支持系统的挑战.
主要成果:
- 结合大数据集和先进的表型识别,AI/ML可以增强早期IEI识别.
- AI/ML模型有可能改善IEI的诊断和管理.
- 在临床环境中实施AI/ML面临着几个挑战.
结论:
- 人工智能/ML具有很大的潜力,可以促进IEI的早期检测和公平护理.
- 需要进一步的研究和开发来克服实施挑战.
- AI/ML可以完善IEI的诊断和管理,改善患者的治疗结果.
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