A newborn screening system based on service-oriented architecture embedded support vector machine.
The clinical symptoms of metabolic disorders are rarely apparent during the neonatal period, and if they are not treated earlier, irreversible damages, such as mental retardation or even death, may occur. Therefore, the practice of newborn screening is essential to prevent permanent disabilities in newborns. In the paper, we design, implement a newborn screening system using Support Vector Machine (SVM) classifications. By evaluating metabolic substances data collected from tandem mass spectrometry (MS/MS), we can interpret and determine whether a newborn has a metabolic disorder. In addition, National Taiwan University Hospital Information System (NTUHIS) has been developed and implemented to integrate heterogeneous platforms, protocols, databases as well as applications. To expedite adapting the diversities, we deploy Service-Oriented Architecture (SOA) concepts to the newborn screening system based on web services. The system can be embedded seamlessly into NTUHIS.
Hsu
Kai-Ping
KP
Department of Computer Science and Information Engineering, National Taiwan University, Taipei, Taiwan.
Hsieh
Sung-Huai
SH
Hsieh
Sheau-Ling
SL
Cheng
Po-Hsun
PH
Weng
Yung-Ching
YC
Wu
Jang-Hung
JH
Lai
Feipei
F
D001185:Artificial Intelligence; D003195:Computer Communication Networks; D057225:Data Mining; D006751:Hospital Information Systems; D006801:Humans; D007231:Infant, Newborn; D008661:Metabolism, Inborn Errors / Q000517:prevention & control*; D015997:Neonatal Screening / Q000295:instrumentation*; D018511:Systems Integration; D013624:Taiwan; D053719:Tandem Mass Spectrometry / Q000295:instrumentation*; D057188:Workflow