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2026

Nyagaka, Felix and Csoban, Tunde and Gichere, Ingrid and Mwaniki, Mukaindo and Kavanagh, Kimberley and Magee, Laura A. and von Dadelszen, Peter and Oindi, Felix (2026) Performance of the Pre-Eclampsia Integrated Estimate of Risk–Machine Learning (PIERS-ML) model in a Kenyan cohort of women with pre-eclampsia- a retrospective test derivation validation study. BMC Pregnancy and Childbirth, 26 (1). 1039. ISSN 1471-2393

Yang, Guiyou and Montgomery-Csobán, Tünde and Lunter, Gerton and Ganzevoort, Wessel and Gordijn, Sanne J. and Murray, Paul and Kavanagh, Kimberley and Magee, Laura and Groen, Henk and von Dadelszen, Peter (2026) Development and external validation of Mini PIERSdynamic Model for predicting the adverse maternal outcome of preeclampsia in low-resource settings. Hypertension. pp. 1-10. ISSN 1524-4563

2025

Yang, Guiyou and Montgomery-Csobán, Tünde and Ganzevoort, Wessel and Gordijn, Sanne J. and Kavanagh, Kimberley and Murray, Paul and Magee, Laura A. and Groen, Henk and von Dadelszen, Peter (2025) Consecutive prediction of adverse maternal outcomes of preeclampsia, using the PIERS-ML and fullPIERS models : a multicountry prospective observational study. PLOS Medicine, 22 (2). e1004509. ISSN 1549-1676

2024

Montgomery-Csobán, Tünde and Kavanagh, Kimberley and Murray, Paul and Robertson, Chris and Barry, Sarah J E and Ukah, U Vivian and Payne, Beth A and Nicolaides, Kypros H and Syngelaki, Argyro and Ionescu, Olivia and Akolekar, Ranjit and Hutcheon, Jennifer A and Magee, Laura A and von Dadelszen, Peter (2024) Machine learning-enabled maternal risk assessment for women with pre-eclampsia (the PIERS-ML model) : a modelling study. The Lancet Digital Health, 6 (4). E238-E250. ISSN 2589-7500