Prediction of gestational diabetes mellitus in Asian women using machine learning algorithms

This study developed a machine learning algorithm to predict gestational diabetes mellitus (GDM) using retrospective data from 34,387 pregnancies in multi-centers of South Korea. Variables were collected at baseline, E0 (until 10 weeks’ gestation), E1 (11–13 weeks’ gestation) and M1 (14–24 weeks’ ge...

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Detalles Bibliográficos
Autores principales: Kang, Byung Soo, Lee, Seon Ui, Hong, Subeen, Choi, Sae Kyung, Shin, Jae Eun, Wie, Jeong Ha, Jo, Yun Sung, Kim, Yeon Hee, Kil, Kicheol, Chung, Yoo Hyun, Jung, Kyunghoon, Hong, Hanul, Park, In Yang, Ko, Hyun Sun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2023
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10432552/
https://www.ncbi.nlm.nih.gov/pubmed/37587201
http://dx.doi.org/10.1038/s41598-023-39680-8

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10432552/
https://www.ncbi.nlm.nih.gov/pubmed/37587201
http://dx.doi.org/10.1038/s41598-023-39680-8

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