A machine learning approach for early prediction of gestational diabetes mellitus using elemental contents in fingernails

The aim of this pilot study was to predict the risk of gestational diabetes mellitus (GDM) by the elemental content in fingernails and urine with machine learning analysis. Sixty seven pregnant women (34 control and 33 GDM patient) were included. Fingernails and urine were collected in the first and...

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Detalles Bibliográficos
Autores principales: Chan, Yun-Nam, Wang, Pengpeng, Chun, Ka-Him, Lum, Judy Tsz-Shan, Wang, Hang, Zhang, Yunhui, Leung, Kelvin Sze-Yin
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/PMC10015050/
https://www.ncbi.nlm.nih.gov/pubmed/36918683
http://dx.doi.org/10.1038/s41598-023-31270-y

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10015050/
https://www.ncbi.nlm.nih.gov/pubmed/36918683
http://dx.doi.org/10.1038/s41598-023-31270-y

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