Prediction model for gestational diabetes mellitus using the XG Boost machine learning algorithm

OBJECTIVE: To develop the extreme gradient boosting (XG Boost) machine learning (ML) model for predicting gestational diabetes mellitus (GDM) compared with a model using the traditional logistic regression (LR) method. METHODS: A case–control study was carried out among pregnant women, who were assi...

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Detalles Bibliográficos
Autores principales: Hu, Xiaoqi, Hu, Xiaolin, Yu, Ya, Wang, Jia
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2023
Materias:
Endocrinology
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10034315/
https://www.ncbi.nlm.nih.gov/pubmed/36967760
http://dx.doi.org/10.3389/fendo.2023.1105062

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10034315/
https://www.ncbi.nlm.nih.gov/pubmed/36967760
http://dx.doi.org/10.3389/fendo.2023.1105062

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