Department of Pathology and Laboratory Medicine, UC Davis School of Medicine, CA.
Department of Emergency Medicine, UC Davis School of Medicine, CA.
Clin Chem. 2021 Dec 30;68(1):125-133. doi: 10.1093/clinchem/hvab239.
Artificial intelligence (AI) and machine learning (ML) are poised to transform infectious disease testing. Uniquely, infectious disease testing is technologically diverse spaces in laboratory medicine, where multiple platforms and approaches may be required to support clinical decision-making. Despite advances in laboratory informatics, the vast array of infectious disease data is constrained by human analytical limitations. Machine learning can exploit multiple data streams, including but not limited to laboratory information and overcome human limitations to provide physicians with predictive and actionable results. As a quickly evolving area of computer science, laboratory professionals should become aware of AI/ML applications for infectious disease testing as more platforms are become commercially available.
In this review we: (a) define both AI/ML, (b) provide an overview of common ML approaches used in laboratory medicine, (c) describe the current AI/ML landscape as it relates infectious disease testing, and (d) discuss the future evolution AI/ML for infectious disease testing in both laboratory and point-of-care applications.
The review provides an important educational overview of AI/ML technique in the context of infectious disease testing. This includes supervised ML approaches, which are frequently used in laboratory medicine applications including infectious diseases, such as COVID-19, sepsis, hepatitis, malaria, meningitis, Lyme disease, and tuberculosis. We also apply the concept of "data fusion" describing the future of laboratory testing where multiple data streams are integrated by AI/ML to provide actionable clinical knowledge.
人工智能（AI）和机器学习（ML）有望改变传染病检测。独特的是，传染病检测是实验室医学中技术多样化的领域，需要多种平台和方法来支持临床决策。尽管实验室信息学取得了进步，但大量的传染病数据受到人类分析能力的限制。机器学习可以利用多种数据流，包括但不限于实验室信息，并克服人类的局限性，为医生提供预测性和可操作的结果。作为计算机科学中一个快速发展的领域，随着越来越多的平台商业化，实验室专业人员应该了解 AI/ML 在传染病检测中的应用。
在这篇综述中，我们：（a）定义了 AI/ML；（b）概述了实验室医学中常用的 ML 方法；（c）描述了与传染病检测相关的当前 AI/ML 领域；（d）讨论了 AI/ML 在实验室和即时检测应用中用于传染病检测的未来发展。
这篇综述在传染病检测的背景下提供了 AI/ML 技术的重要教育概述。这包括监督 ML 方法，这些方法在包括 COVID-19、败血症、肝炎、疟疾、脑膜炎、莱姆病和结核病在内的传染病等实验室医学应用中经常使用。我们还应用了“数据融合”的概念，描述了实验室检测的未来，即通过 AI/ML 整合多个数据流以提供可操作的临床知识。
