Interpretable Machine Learning Framework Reveals Robust Gut Microbiome Features Associated With Type 2 Diabetes | Zendy

Wanglong Gou | Zendy; Chu-wen Ling | Zendy; Yan He | Zendy; Zengliang Jiang | Zendy; Yuanqing Fu | Zendy; Fengzhe Xu | Zendy; Zelei Miao | Zendy; Tingyu Sun | Zendy; Jie-sheng Lin | Zendy; Huilian Zhu | Zendy; Hongwei Zhou | Zendy; YuMing Chen | Zendy; JuSheng Zheng | Zendy

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Interpretable Machine Learning Framework Reveals Robust Gut Microbiome Features Associated With Type 2 Diabetes

Author(s) -

Wanglong Gou,

Chu-wen Ling,

Yan He,

Zengliang Jiang,

Yuanqing Fu,

Fengzhe Xu,

Zelei Miao,

Tingyu Sun,

Jie-sheng Lin,

Huilian Zhu,

Hongwei Zhou,

YuMing Chen,

JuSheng Zheng

Publication year - 2020

Publication title -

diabetes care

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 6.636

H-Index - 363

eISSN - 1935-5548

pISSN - 0149-5992

DOI - 10.2337/dc20-1536

Subject(s) - type 2 diabetes , medicine , microbiome , diabetes mellitus , prospective cohort study , cohort , gut flora , cohort study , body mass index , feces , physiology , endocrinology , bioinformatics , immunology , biology , paleontology

To identify the core gut microbial features associated with type 2 diabetes risk and potential demographic, adiposity, and dietary factors associated with these features.

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