Cargando…
A Framework for Effective Application of Machine Learning to Microbiome-Based Classification Problems
Machine learning (ML) modeling of the human microbiome has the potential to identify microbial biomarkers and aid in the diagnosis of many diseases such as inflammatory bowel disease, diabetes, and colorectal cancer. Progress has been made toward developing ML models that predict health outcomes usi...
Autores principales: | Topçuoğlu, Begüm D., Lesniak, Nicholas A., Ruffin, Mack T., Wiens, Jenna, Schloss, Patrick D. |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
American Society for Microbiology
2020
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7373189/ https://www.ncbi.nlm.nih.gov/pubmed/32518182 http://dx.doi.org/10.1128/mBio.00434-20 |
Ejemplares similares
-
Machine learning classification by fitting amplicon sequences to existing OTUs
por: Armour, Courtney R., et al.
Publicado: (2023) -
Fecal Short-Chain Fatty Acids Are Not Predictive of Colonic Tumor Status and Cannot Be Predicted Based on Bacterial Community Structure
por: Sze, Marc A., et al.
Publicado: (2019) -
mikropml: User-Friendly R Package for Supervised Machine Learning Pipelines
por: Topçuoğlu, Begüm D., et al.
Publicado: (2021) -
A Goldilocks Principle for the Gut Microbiome: Taxonomic Resolution Matters for Microbiome-Based Classification of Colorectal Cancer
por: Armour, Courtney R., et al.
Publicado: (2022) -
The Glucoamylase Inhibitor Acarbose Has a Diet-Dependent and Reversible Effect on the Murine Gut Microbiome
por: Baxter, Nielson T., et al.
Publicado: (2019)