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Deleterious and Protective Psychosocial and Stress-Related Factors Predict Risk of Spontaneous Preterm Birth, , , , , , , , , and 3 other author(s). American journal of perinatology, (May 2021)Deep representation learning identifies associations between physical activity and sleep patterns during pregnancy and prematurity., , , , , , , , , and 11 other author(s). npj Digit. Medicine, (2023)A data-driven health index for neonatal morbidities, , , , , , , , , and 11 other author(s). iScience, (2022)Multiomics Characterization of Preterm Birth in Low- and Middle-Income Countries, , , , , , , , , and 68 other author(s). JAMA Network Open, (2020)Integration of mechanistic immunological knowledge into a machine learning pipeline improves predictions., , , , , , , , , and 21 other author(s). Nat. Mach. Intell., 2 (10): 619-628 (2020)Replication and refinement of a vaginal microbial signature of preterm birth in two racially distinct cohorts of US women, , , , , , , , , and 1 other author(s). Proceedings of the National Academy of Sciences, 114 (37): 9966--9971 (2017)Data-Driven Modeling of Pregnancy-Related Complications, , , , , , , , , and 7 other author(s). Trends in Molecular Medicine, (2021)Integrated trajectories of the maternal metabolome, proteome, and immunome predict labor onset, , , , , , , , , and 28 other author(s). Science Translational Medicine, (2021)Early prediction and longitudinal modeling of preeclampsia from multiomics., , , , , , , , , and 23 other author(s). Patterns, 3 (12): 100655 (2022)Data-driven longitudinal characterization of neonatal health and morbidity, , , , , , , , , and 23 other author(s). Science Translational Medicine, 15 (683): eadc9854 (2023)