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Female Urogenital Diseases and Pregnancy Complications Commons™
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Full-Text Articles in Female Urogenital Diseases and Pregnancy Complications
Machine Learning Guided Postnatal Gestational Age Assessment Using New-Born Screening Metabolomic Data In South Asia And Sub-Saharan Africa, Sunil Sazawal, Kelli K. Ryckman, Sayan Das, Muhammad Imran Nisar, Usma Mehmood, Amina Barkat, Farah Khalid, Muhammad Ilyas Muhammad Ilyas, Ambreen Nizar, Fyezah Jehan
Machine Learning Guided Postnatal Gestational Age Assessment Using New-Born Screening Metabolomic Data In South Asia And Sub-Saharan Africa, Sunil Sazawal, Kelli K. Ryckman, Sayan Das, Muhammad Imran Nisar, Usma Mehmood, Amina Barkat, Farah Khalid, Muhammad Ilyas Muhammad Ilyas, Ambreen Nizar, Fyezah Jehan
Department of Paediatrics and Child Health
Background: Babies born early and/or small for gestational age in Low and Middle-income countries (LMICs) contribute substantially to global neonatal and infant mortality. Tracking this metric is critical at a population level for informed policy, advocacy, resources allocation and program evaluation and at an individual level for targeted care. Early prenatal ultrasound examination is not available in these settings, gestational age (GA) is estimated using new-born assessment, last menstrual period (LMP) recalls and birth weight, which are unreliable. Algorithms in developed settings, using metabolic screen data, provided GA estimates within 1-2 weeks of ultrasonography-based GA. We sought to leverage machine …