Machine learning approaches to predict gestational age in normal and complicated pregnancies via urinary metabolomics analysis

The elucidation of dynamic metabolomic changes during gestation is particularly important for the development of methods to evaluate pregnancy status or achieve earlier detection of pregnancy-related complications. Some studies have constructed models to evaluate pregnancy status and predict gestati...

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Detalles Bibliográficos
Autores principales: Yamauchi, Takafumi, Ochi, Daisuke, Matsukawa, Naomi, Saigusa, Daisuke, Ishikuro, Mami, Obara, Taku, Tsunemoto, Yoshiki, Kumatani, Satsuki, Yamashita, Riu, Tanabe, Osamu, Minegishi, Naoko, Koshiba, Seizo, Metoki, Hirohito, Kuriyama, Shinichi, Yaegashi, Nobuo, Yamamoto, Masayuki, Nagasaki, Masao, Hiyama, Satoshi, Sugawara, Junichi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2021
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8423760/
https://www.ncbi.nlm.nih.gov/pubmed/34493809
http://dx.doi.org/10.1038/s41598-021-97342-z

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8423760/
https://www.ncbi.nlm.nih.gov/pubmed/34493809
http://dx.doi.org/10.1038/s41598-021-97342-z

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