Identification and Optimization of Contributing Factors for Precocious Puberty by Machine/Deep Learning Methods in Chinese Girls

BACKGROUND AND OBJECTIVES: As the worldwide secular trends are toward earlier puberty, identification of contributing factors for precocious puberty is critical. We aimed to identify and optimize contributing factors responsible for onset of precocious puberty via machine learning/deep learning algo...

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Detalles Bibliográficos
Autores principales: Pang, Bo, Wang, Qiong, Yang, Min, Xue, Mei, Zhang, Yicheng, Deng, Xiangling, Zhang, Zhixin, Niu, Wenquan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Endocrinology
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9279618/
https://www.ncbi.nlm.nih.gov/pubmed/35846287
http://dx.doi.org/10.3389/fendo.2022.892005

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9279618/
https://www.ncbi.nlm.nih.gov/pubmed/35846287
http://dx.doi.org/10.3389/fendo.2022.892005

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