A stepwise prediction and interpretation of gestational diabetes mellitus: Foster the practical application of machine learning in clinical decision

A stepwise prediction and interpretation of gestational diabetes mellitus: Foster the practical application of machine learning in clinical decision

Background: Machine learning has shown to be an effective method for early prediction and intervention of Gestational diabetes mellitus (GDM), which greatly decreases GDM incidence, reduces maternal and infant complications and improves the prognosis. However, there is still much room for improvemen...

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Bibliographic Details
Main Authors: Fang Zhou, Xiao Ran, Fangliang Song, Qinglan Wu, Yuan Jia, Ying Liang, Suichen Chen, Guojun Zhang, Jie Dong, Yukun Wang
Format: Article
Language:English
Published: Elsevier 2024-06-01
Series:Heliyon
Subjects:
Gestational diabetes mellitus
Machine learning
Risk prediction
Model explanation
Computational medicine
Online Access:http://www.sciencedirect.com/science/article/pii/S2405844024087401

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http://www.sciencedirect.com/science/article/pii/S2405844024087401

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