Reducing False-Positive Results in Newborn Screening Using Machine Learning
Peng G, Tang Y, Cowan TM, Enns GM, Zhao H, Scharfe C. Reducing False-Positive Results in Newborn Screening Using Machine Learning. International Journal Of Neonatal Screening 2020, 6: 16. PMID: 32190768, PMCID: PMC7080200, DOI: 10.3390/ijns6010016.Peer-Reviewed Original ResearchOrnithine transcarbamylase deficiencyMethylmalonic acidemiaNewborn screeningGlutaric acidemia type 1Successful public health programsLong-chain acyl-CoA dehydrogenase deficiencyPublic health programsInborn metabolic disordersAcyl-CoA dehydrogenase deficiencyGestational ageClinical variablesFalse-positive resultsBirth weightMetabolic disordersScreen positivesHealth programsType 1NBS programsDehydrogenase deficiencyDisease markersDisordersPositive resultsScreening