Comparison of machine learning and conventional logistic regression-based prediction models for gestational diabetes in an ethnically diverse population; the Monash GDM Machine learning model-Reference-Cited by-同舟云学术

Comparison of machine learning and conventional logistic regression-based prediction models for gestational diabetes in an ethnically diverse population; the Monash GDM Machine learning model

Published:2023-11 Issue: Volume:179 Page:105228
ISSN:1386-5056
Container-title:International Journal of Medical Informatics
language:en
Short-container-title:International Journal of Medical Informatics

Author:

Belsti Yitayeh^ORCID,Moran Lisa,Du Lan^ORCID,Mousa Aya^ORCID,De Silva Kushan,Enticott Joanne^ORCID,Teede Helena

Funder

National Health and Medical Research Council

Publisher

Elsevier BV

Subject

Health Informatics

Reference53 articles.

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3. IDF diabetes Atlas: estimation of global and regional gestational diabetes mellitus prevalence for 2021 by international association of diabetes in pregnancy study Group’s criteria;Wang;Diabetes Res. Clin. Pract.,2022

4. IDF Diabetes Atlas: global estimates for the prevalence of diabetes for 2015 and 2040;Ogurtsova;Diabetes Res. Clin. Pract.,2017

5. IDF Diabetes Atlas: global estimates of diabetes prevalence for 2017 and projections for 2045;Cho;Diabetes Res. Clin. Pract.,2018

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1. Routine screening for gestational diabetes: a review;Current Opinion in Obstetrics & Gynecology;2024-01-16