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Evolving Applications of Artificial Intelligence and Machine Learning in Infectious Diseases Testing
Clinical Chemistry ( IF 7.1 ) Pub Date : 2021-10-27 , DOI: 10.1093/clinchem/hvab239
Nam K Tran 1 , Samer Albahra 1 , Larissa May 2 , Sarah Waldman 3 , Scott Crabtree 3 , Scott Bainbridge 1 , Hooman Rashidi 1
Affiliation  

Background 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. Content 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. Summary 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.

中文翻译:

人工智能和机器学习在传染病检测中不断发展的应用

背景 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空间,可能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展,但大量传染病数据仍受到人类分析限制的限制。机器学习可以利用多个数据流,包括但不限于实验室信息,并克服人为限制,为医生提供可预测和可操作的结果。作为一个快速发展的计算机科学领域,随着更多平台的商业化,实验室专业人员应该意识到用于传染病检测的 AI/ML 应用。内容在这篇评论中,我们:(a) 定义 AI/ML,(b) 概述实验室医学中使用的常见 ML 方法,(c) 描述当前与传染病检测相关的 AI/ML 格局,以及 (d ) 讨论未来 AI/ML 在实验室和护理点应用中用于传染病检测的演进。总结 本综述提供了在传染病检测背景下对 AI/ML 技术的重要教育概述。这包括有监督的机器学习方法,这些方法经常用于实验室医学应用,包括传染病,如 COVID-19、败血症、肝炎、疟疾、脑膜炎、莱姆病和肺结核。
更新日期:2021-10-27
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