Interpretable machine learning-derived nomogram model for early detection of diabetic retinopathy in type 2 diabetes mellitus: a widely targeted metabolomics study

OBJECTIVE: Early identification of diabetic retinopathy (DR) is key to prioritizing therapy and preventing permanent blindness. This study aims to propose a machine learning model for DR early diagnosis using metabolomics and clinical indicators. METHODS: From 2017 to 2018, 950 participants were enr...

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Detalles Bibliográficos
Autores principales: Li, Jushuang, Guo, Chengnan, Wang, Tao, Xu, Yixi, Peng, Fang, Zhao, Shuzhen, Li, Huihui, Jin, Dongzhen, Xia, Zhezheng, Che, Mingzhu, Zuo, Jingjing, Zheng, Chao, Hu, Honglin, Mao, Guangyun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9355962/
https://www.ncbi.nlm.nih.gov/pubmed/35931671
http://dx.doi.org/10.1038/s41387-022-00216-0

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9355962/
https://www.ncbi.nlm.nih.gov/pubmed/35931671
http://dx.doi.org/10.1038/s41387-022-00216-0

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