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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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| Опубликовано в: : | JAMIA Open |
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| Главные авторы: | , , , |
| Формат: | Artigo |
| Язык: | Inglês |
| Опубликовано: |
Oxford University Press
2020
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| Предметы: | |
| Online-ссылка: | https://ncbi.nlm.nih.gov/pmc/articles/PMC7886559/ https://ncbi.nlm.nih.gov/pubmed/33623892 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1093/jamiaopen/ooaa063 |
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