Interpretable machine learning algorithms reveal gut microbiome features associated with atopic dermatitis
Machine learning models combined with SHAP could be used to quantitatively screen key gut flora in atopic dermatitis patients, providing doctors with an intuitive understanding of 16S rRNA sequencing data to support precision medicine in care and recovery.
Authors
- Shiqi Li (ORCID: https://orcid.org/0000-0002-0475-9781)
- Lilian Zeng
- Wei Wu (ORCID: https://orcid.org/0000-0001-7371-2963)
- Xingfen Yang (ORCID: https://orcid.org/0000-0001-5806-4507)
- Zhifeng Li (ORCID: https://orcid.org/0000-0002-7647-0880)
- Jing Ma (ORCID: https://orcid.org/0000-0003-2067-2923)
- Siyi Chen (ORCID: https://orcid.org/0000-0002-2770-4193)
- Yi‐Ting Fang (ORCID: https://orcid.org/0000-0002-2845-8799)
- Guiyuan Ji
Institutions
- Guangdong Provincial Center for Disease Control and Prevention (CN)
- Southern Medical University (CN)
Publication Details
- Journal
- Frontiers in Immunology
- Published
- 2025-05-01
- DOI
- https://doi.org/10.3389/fimmu.2025.1528046
- Citations
- 5
- Primary Topic
- Gut microbiota and health
- Type
- article
- Field-Weighted Citation Impact
- 4.03
Funders
- National Natural Science Foundation of China
- National Key Scientific Instrument and Equipment Development Projects of China