Machine learning identifies girls with central precocious puberty based on multisource data

OBJECTIVE: The study aimed to develop simplified diagnostic models for identifying girls with central precocious puberty (CPP), without the expensive and cumbersome gonadotropin-releasing hormone (GnRH) stimulation test, which is the gold standard for CPP diagnosis. MATERIALS AND METHODS: Female pat...

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Detalles Bibliográficos
Autores principales: Pan, Liyan, Liu, Guangjian, Mao, Xiaojian, Liang, Huiying
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2020
Materias:
Research and Applications
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7886559/
https://www.ncbi.nlm.nih.gov/pubmed/33623892
http://dx.doi.org/10.1093/jamiaopen/ooaa063

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7886559/
https://www.ncbi.nlm.nih.gov/pubmed/33623892
http://dx.doi.org/10.1093/jamiaopen/ooaa063

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