Use of uterine activity to predict preterm birth by artificial intelligence assisted models: a narrative systematic review

Objective The benefit of interventions to improve neonatal outcomes of preterm birth (PTB) must be balanced with the associated fetal and maternal risks. Artificial intelligence (AI) could be used to assess uterine contractions and consequently help to predict PTB. This paper aims to assess the pred...

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Bibliografski detalji

Glavni autori:	Jagrati Chopra, Charlotte Maden, Isabel Howlett, Helen Perry, Alexandra J. Kermack, Mehtap Ozbey Arabaci, Adriane Chapman, Kai Yang, Diego Altamirano, Ying Cheong
Format:	Artigo
Jezik:	Inglês
Izdano:	Taylor & Francis Group 2026-12-01
Serija:	The Journal of Maternal-Fetal & Neonatal Medicine
Teme:	Preterm birth preterm labor electrohysterography artificial intelligence machine learning deep neural networks
Online pristup:	https://www.tandfonline.com/doi/10.1080/14767058.2025.2582375
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