Prediction of gestational diabetes using deep learning and Bayesian optimization and traditional machine learning techniques

The study aimed to develop a clinical diagnosis system to identify patients in the GD risk group and reduce unnecessary oral glucose tolerance test (OGTT) applications for pregnant women who are not in the GD risk group using deep learning algorithms. With this aim, a prospective study was designed...

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Detalles Bibliográficos
Autores principales: Kurt, Burçin, Gürlek, Beril, Keskin, Seda, Özdemir, Sinem, Karadeniz, Özlem, Kırkbir, İlknur Buçan, Kurt, Tuğba, Ünsal, Serbülent, Kart, Cavit, Baki, Neslihan, Turhan, Kemal
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Berlin Heidelberg 2023
Materias:
Original Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9969040/
https://www.ncbi.nlm.nih.gov/pubmed/36848010
http://dx.doi.org/10.1007/s11517-023-02800-7

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9969040/
https://www.ncbi.nlm.nih.gov/pubmed/36848010
http://dx.doi.org/10.1007/s11517-023-02800-7

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