Explainable predictive models of short stature and exploration of related environmental growth factors: a case-control study

Abstract Background Short stature is a prevalent pediatric endocrine disorder for which early detection and prediction are pivotal for improving treatment outcomes. However, existing diagnostic criteria often lack the necessary sensitivity and specificity because of the complex etiology of the disor...

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Detalhes bibliográficos

Principais autores:	Jiani Liu, Xin Zhang, Wei Li, Francis Manyori Bigambo, Dandan Wang, Xu Wang, Beibei Teng
Formato:	Artigo
Idioma:	Inglês
Publicado em:	BMC 2025-05-01
coleção:	BMC Endocrine Disorders
Assuntos:	Short stature Machine learning Predictive model Growth environment SHAP
Acesso em linha:	https://doi.org/10.1186/s12902-025-01936-x
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