Hsieh, S.-H.S.-H.HsiehCheng, P.-H.P.-H.ChengChen, C.-H.C.-H.ChenHuang, K.-H.K.-H.HuangChen, P.-H.P.-H.ChenWeng, Y.-C.Y.-C.WengHsieh, S.-L.S.-L.HsiehFEI-PEI LAI2020-04-162020-04-162010https://scholars.lib.ntu.edu.tw/handle/123456789/484435The clinical symptoms of metabolic disorders during neonatal period are often not apparent. If not treated early, irreversible damages such as mental retardation may occur, even death. Therefore, practicing newborn screening is essential, imperative to prevent neonatal from these damages. In the paper, we establish a newborn screening model that utilizes Support Vector Machines (SVM) techniques and enhancements to evaluate, interpret the Methylmalonic Acidemia (MMA) metabolic disorders. The model encompasses the Feature Selections, Grid Search, Cross Validations as well as multi model Voting Mechanism. In the model, the predicting accuracy, sensitivity and specificity of MMA can be improved dramatically. The model will be able to apply to other metabolic diseases as well. ? 2009 Springer Science+Business Media, LLC.Methylmalonic acidemia; Newborn screening; Support vector machines; Tandem mass spectrometry[SDGs]SDG3methylmalonic acid; article; diagnostic accuracy; health care system; medical information; medical instrumentation; metabolic disorder; methyl malonic acidemia; newborn screening; sensitivity and specificity; algorithm; blood; Brain Diseases, Metabolic, Inborn; evaluation study; human; newborn; signal processing; tandem mass spectrometry; urine; Algorithms; Brain Diseases, Metabolic, Inborn; Humans; Infant, Newborn; Methylmalonic Acid; Neonatal Screening; Sensitivity and Specificity; Signal Processing, Computer-Assisted; Tandem Mass Spectrometry; Algorithms; Brain Diseases, Metabolic, Inborn; Humans; Infant, Newborn; Methylmalonic Acid; Neonatal Screening; Sensitivity and Specificity; Signal Processing, Computer-Assisted; Tandem Mass Spectrometryjournal article10.1007/s10916-009-9287-42-s2.0-77956056616https://www.scopus.com/inward/record.uri?eid=2-s2.0-77956056616&doi=10.1007%2fs10916-009-9287-4&partnerID=40&md5=cbb8bca36e2b19ed5856efb6a72987c4