This paper is in the following e-collection/theme issue:

Authors' Responses to Peer-Reviews (90)

Published on in Vol 5 (2024)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/60174, first published .
Authors’ Response to Peer Reviews of “Machine Learning–Based Hyperglycemia Prediction: Enhancing Risk Assessment in a Cohort of Undiagnosed Individuals”

Authors’ Response to Peer Reviews of “Machine Learning–Based Hyperglycemia Prediction: Enhancing Risk Assessment in a Cohort of Undiagnosed Individuals”

Authors’ Response to Peer Reviews of “Machine Learning–Based Hyperglycemia Prediction: Enhancing Risk Assessment in a Cohort of Undiagnosed Individuals”

Authors of this article:

Kolapo Oyebola1, 2 Author Orcid Image ;   Funmilayo Ligali1, 2 Author Orcid Image ;   Afolabi Owoloye1, 2 Author Orcid Image ;   Blessing Erinwusi2 Author Orcid Image ;   Yetunde Alo2 Author Orcid Image ;   Adesola Z Musa1 Author Orcid Image ;   Oluwagbemiga Aina1 Author Orcid Image ;   Babatunde Salako1 Author Orcid Image
Article Authors Cited by Tweetations Metrics

Kolapo Oyebola   1, 2 , DPhil ;   Funmilayo Ligali   1, 2 , MS ;   Afolabi Owoloye   1, 2 , MS ;   Blessing Erinwusi   2 , MS ;   Yetunde Alo   2 , MS ;   Adesola Z Musa   1 , DPhil ;   Oluwagbemiga Aina   1 , DPhil ;   Babatunde Salako   1 , Dr med

1 Nigerian Institute of Medical Research, Lagos, Nigeria

2 Centre for Genomic Research in Biomedicine, Mountain Top University, Ibafo, Nigeria

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