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Editorial Note: Machine learning-driven Diabetes Health Tracer (DHT): Optimizing prognosis using RaSK_GraDe and RaSK_GraDeL models

  • The PLOS One Editors

The PLOS One Editors issue this Editorial Note to inform readers that the work cited in this article [1] as Reference 32 was retracted before the publication date of [1]. PLOS considers that this reference is not crucial in supporting the research or conclusions reported in [1], but the following sentences are no longer supported:

  • Section 2 Literature Review, paragraph 15, sentence 1: “In [32], the author developed the intelligent diabetes mellitus prediction framework (IDMPF), a framework for diabetes prediction. The Pima dataset was utilised by them. The achieved accuracy was 83%. However, the model gives result but not so good, so their is a way to make it better.”

We regret that the issues were not identified prior to the article’s publication.

Reference

  1. 1. Noman M, Hanif M, Hameed A, Babar M, Qureshi B. Machine learning-driven Diabetes Health Tracer (DHT): Optimizing prognosis using RaSK_GraDe and RaSK_GraDeL models. PLoS One. 2025;20(10):e0327661. pmid:41118429