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F. Facchinetti

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Open access Oct 2026

Limits of Machine Learning for Predicting Stillbirth at Term: A Population-Based Cohort of 302,192 Pregnancies in Northern Italy.

BACKGROUND Stillbirth at term is a major public-health concern. In high-income settings, the most commonly identifiable causes are unrecognised fetal growth restriction (about 14%) and placental abruption (about 12%), but 20 to 40% of term stillbirths remain unexplained. Whether modern machine learning can substantivel...

M. Benuzzi, T. Kawakita, F. Monari et al. · 0 citations

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