A Multi-Voting Enhancement for Newborn Screening Healthcare Information System

作者：Hsieh Sung Huai; Cheng Po Hsun^*; Chen Chi Huang; Huang Kuo Hsuan; Chen Po Hao; Weng Yung Ching; Hsieh Sheau Ling; Lai Feipei

来源：Journal of Medical Systems, 2010, 34(4): 727-733.

DOI：10.1007/s10916-009-9287-4

• Newborn screening
• Tandem mass spectrometry
• Support vector machines
• Methylmalonic acidemia

The 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.

• 出版日期2010-8