DocumentCode :
1784943
Title :
Genetic testing knowledge base (GTKB) towards individualized genetic test recommendation — An experimental study
Author :
Qian Zhu ; Hongfang Liu ; Chute, Christopher G. ; Ferber, Matthew
Author_Institution :
Dept. of Inf. Syst., Univ. of Maryland Baltimore, Baltimore, MD, USA
fYear :
2014
fDate :
2-5 Nov. 2014
Firstpage :
574
Lastpage :
577
Abstract :
The gap between a large growing number of genetic tests and a suboptimal clinical workflow of incorporating these tests into regular clinical practice poses barriers to effective reliance on advanced genetic technologies to improve quality of healthcare. A promising solution to encourage and assist physicians to incorporate genetic tests in their clinical practice is an intelligent genetic test recommendation system for 1) providing a comprehensive view of genetic tests as education resources; 2) recommending the most appropriate genetic tests to patients based on clinical evidence. In this paper, we introduce a genetic testing knowledge base, called GTKB, which was designed to support further individualized genetic test recommendation. More specifically, we extracted clinical characteristics identified from Electronic Health Records (EHRs) that have been used as phenotypic information for linked archived biological material to accelerate research in individualized medicine, and well-documented public genetic testing resources including Genetic Testing Registry (GTR) and published genetic testing guidelines (GTG) to construct a genetic test orientated knowledge base, ultimately supporting genetic test recommendation. An experimental study for “wilson disease mutation screen test” has been conducted to demonstrate the identification of salient clinical characteristics and the process of incorporating EHR derived phenotypes into the GTKB construction.
Keywords :
diseases; electronic health records; genetics; health care; EHR; GTG; GTKB construction; GTR; biological material; education resource; electronic health record; experimental study; genetic technology; genetic test recommendation system; genetic testing guideline; genetic testing knowledge base; genetic testing registry; healthcare quality improvement; individualized genetic test recommendation; individualized medicine; public genetic testing resource; salient clinical characteristics; suboptimal clinical workflow; wilson disease mutation screen test; Diseases; Feature extraction; Genetics; Medical diagnostic imaging; Testing; Wavelength division multiplexing; Genetic test; Individualized medicine; electronic health record; wilson disease;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Bioinformatics and Biomedicine (BIBM), 2014 IEEE International Conference on
Conference_Location :
Belfast
Type :
conf
DOI :
10.1109/BIBM.2014.6999223
Filename :
6999223
Link To Document :
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