Machine learning applications in microbial ecology, human microbiome studies, and environmental monitoring

Advances in nucleic acid sequencing technology have enabled expansion of our ability to profile microbial diversity. These large datasets of taxonomic and functional diversity are key to better understanding microbial ecology. Machine learning has proven to be a useful approach for analyzing microbial community data and making predictions about outcomes including human and environmental health. Machine learning applied to microbial community profiles has been used to predict disease states in hu

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ethics.ai (1 January 2021), “Machine learning applications in microbial ecology, human microbiome studies, and environmental monitoring,” evidence record 9022, https://ethics.ai/record/9022 (originally published by OpenAlex).

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