Abstract
Advanced computational approaches in artificial intelligence, such as machine learning, have been increasingly applied in life sciences and healthcare to analyze large-scale complex biological data, such as microbiome data. In this chapter, we describe the experimental procedures for using microbiome-based machine learning models for phenotypic classification.
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Acknowledgments
This work was supported by the National Heart, Lung and Blood Institute of the National Institutes of Health (R01HL143082).
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Cheng, X., Joe, B. (2023). Artificial Intelligence in Medicine: Microbiome-Based Machine Learning for Phenotypic Classification. In: Mitra, S. (eds) Metagenomic Data Analysis. Methods in Molecular Biology, vol 2649. Humana, New York, NY. https://doi.org/10.1007/978-1-0716-3072-3_14
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DOI: https://doi.org/10.1007/978-1-0716-3072-3_14
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