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. 2022 Apr 22;54(4):466–482. doi: 10.1038/s12276-022-00748-6

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© The Author(s) 2022

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

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Fig. 3 — Precision medicine goals, including risk assessment, screening, prediction, and monitoring, are based on analysis using an artificial intelligence (AI) algorithm through human microbial EV big data and clinical data. High-risk individuals and diseased individuals can be identified by risk assessment, and preventive therapy can reduce disease risk. Diseased individuals identified by screening and diagnosis are suggested therapeutics based on the results of response prediction and monitoring. These processes can realize microbial EV-based health care solutions.