An enhanced machine learning algorithm for type 2 diabetes prognosis with a detailed examination of...
An enhanced machine learning algorithm for type 2 diabetes prognosis with a detailed examination of Key correlates
About this item
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Author / Creator
Wang, Xueyan , Shen, Ping , Zhao, Guoxu , Li, Jiahang , Zhu, Yanfei , Li, Ying , Xu, Hongna , Liu, Jiaqi and Cui, Rongjun
Publisher
London: Nature Publishing Group UK
Journal title
Language
English
Formats
Publication information
Publisher
London: Nature Publishing Group UK
Subjects
More information
Scope and Contents
Contents
This study aimed to construct a high-performance prediction and diagnosis model for type 2 diabetic retinopathy (DR) and identify key correlates of DR. This study utilized a cross-sectional dataset of 3,000 patients from the People’s Liberation Army General Hospital in 2021. Logistic regression was used as the baseline model to compare the predicti...
Alternative Titles
Full title
An enhanced machine learning algorithm for type 2 diabetes prognosis with a detailed examination of Key correlates
Authors, Artists and Contributors
Author / Creator
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Primary Identifiers
Record Identifier
TN_cdi_doaj_primary_oai_doaj_org_article_be37683fef354bb68f5bc3d8a61972f4
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_be37683fef354bb68f5bc3d8a61972f4
Other Identifiers
ISSN
2045-2322
E-ISSN
2045-2322
DOI
10.1038/s41598-024-75898-w
