標題: 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
資訊技術服務中心
Information Technology Services Center
關鍵字: Newborn screening;Tandem mass spectrometry;Support vector machines;Methylmalonic acidemia
公開日期: 1-Aug-2010
摘要: 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.
URI: http://dx.doi.org/10.1007/s10916-009-9287-4
http://hdl.handle.net/11536/32365
ISSN: 0148-5598
DOI: 10.1007/s10916-009-9287-4
期刊: JOURNAL OF MEDICAL SYSTEMS
Volume: 34
Issue: 4
起始頁: 727
結束頁: 733
Appears in Collections:Articles


Files in This Item:

  1. 000280071200033.pdf