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Predicting spontaneous preterm birth using machine learning algorithms

OBJECTIVE: To identify risk factors for spontaneous preterm birth(sPTB)and establish a predictive model in ethnic minority populations of Yunnan Province, China.STUDY DESIGN This prospective cohort study included pregnant women from a tertiary hospital in Kunming between 2022 and 2023. Demographic c...

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Principais autores: Xiaoyan Ma, Nan Li, Yuanting Zhang, Fan Qin, Manrong Li, Yin Gao, Wanqin Hu, Ying Chen
Formato: Artigo
Idioma:Inglês
Publicado em: Taylor & Francis Group 2026-12-01
Colecção:The Journal of Maternal-Fetal & Neonatal Medicine
Assuntos:
Spontaneous preterm birth
prediction model
machine learning
cervical ultrasound elastography
risk factors
Acesso em linha:https://www.tandfonline.com/doi/10.1080/14767058.2026.2667656
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