Supervised machine learning for microbiomics: Bridging the gap between current and best practices

Machine learning (ML) is poised to drive innovations in clinical microbiomics, such as in disease diagnostics and prognostics. However, the successful implementation of ML in these domains necessitates the development of reproducible, interpretable models that meet the rigorous performance standards...

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Bibliographic Details
Main Authors: Natasha Katherine Dudek, Mariami Chakhvadze, Saba Kobakhidze, Omar Kantidze, Yuriy Gankin
Format: Article
Language:English
Published: Elsevier 2024-12-01
Series:Machine Learning with Applications
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Online Access:http://www.sciencedirect.com/science/article/pii/S2666827024000835
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