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Decoding diabetic retinopathy risk through hybrid modeling: integrative assessment of machine learning algorithms and advanced regression frameworks leveraging estimated glucose disposal rate (eGDR)

Crossref DOI link: https://doi.org/10.1007/s40200-025-01765-8

Published Online: 2025-11-05

Update policy: https://doi.org/10.1007/springer_crossmark_policy

Authors

Bahreiny, Seyed Sobhan

Khaksar, Mohammad Ali

Kazemzadeh, Razieh

Mohammadpour fard, Reza

Radmehr, Vahid

Zahedian, Mehdi
License Information

Text and Data Mining valid from 2025-11-05

Version of Record valid from 2025-11-05
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Article History

Received: 15 August 2025

Accepted: 9 October 2025

First Online: 5 November 2025

Declarations

:

: All data gathered during this study were from the National Health and Nutrition Examination Survey (NHANES). The Ethics Review Board of the National Center for Health Statistics approved all NHANES protocols, and written informed consent was obtained from each participant.

: Not applicable.

: The authors declare no competing interests.

: Not applicable.

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