AI for Maternal & Neonatal Health

We develop and apply machine learning methods with a goal to improve pregnancy outcomes for the mom and the baby. We are focused on solutions that are applicable worldwide and especially in low-resource settings.

Research Highlights

Machine learning reveals metabolic profiles of small-for-gestational age infants in low-and middle-income countries (LMICs)
Marić I, Darmstadt G, Ward V et al. PAS (2024)

Discovery of sparse, reliable omic biomarkers with Stabl
Hedou J, Marić I, Bellan G et al. Nature Biotechology (2024)

Early prediction and longitudinal modeling of preeclampsia from multiomics
Marić I, Contrepois K et al., Patterns (2022)

Mortality risk among patients with COVID-19 prescribed selective serotonin reuptake inhibitor antidepressants 
Oskotsky T, Marić I. et al., JAMA Network Open (2021)

Early prediction of preeclampsia via machine learning
Marić I. Tsur A et al., Am J Obstet Gynecol MFM (2020)