Opportunities and challenges in machine learning‐based newborn screening—A systematic literature reviewElaine Zaunseder, Vincent Heuveline, Stefan Kölker et al.|JIMD Reports|2022Cited by 29
Personalized metabolic whole-body models for newborns and infants predict growth and biomarkers of inherited metabolic diseasesElaine Zaunseder, Ines Thiele, Ulrike Mütze et al.|Cell Metabolism|2024Cited by 21
Machine Learning Methods Improve Specificity in Newborn Screening for Isovaleric AciduriaElaine Zaunseder, Stefan Kölker, Ulrike Mütze et al.|Metabolites|2023Cited by 18
Personalised metabolic whole-body models for newborns and infants predict growth and biomarkers of inherited metabolic diseasesElaine Zaunseder, Ines Thiele, Ulrike Mütze et al.|bioRxiv (Cold Spring Harbor Laboratory)|2023Cited by 2
Deep Learning and Explainable Artificial Intelligence for Improving Specificity and Detecting Metabolic Patterns in Newborn ScreeningElaine Zaunseder, Vincent Heuveline, Ulrike Mütze et al.|Unknown|2023Cited by 1