DocumentCode :
190994
Title :
An integrated model of human Biomedical and Clinical Data structures
Author :
Paliulis, Egidijus ; Ali, Hazem H.
Author_Institution :
Dept. of Inf. Technol., Siauliai Univ., Siauliai, Lithuania
fYear :
2014
fDate :
2-4 June 2014
Firstpage :
1
Lastpage :
6
Abstract :
The Biomedical and Clinical (BC) research domain has evolved significantly in the last decade, quickly becoming a data-intensive field that requires sophisticated databases and data analysis tools. The constant growth of BC data has given rise to the notion of data-driven decision making. BC institutions typically use a wide range of modern diagnostic equipment that produces various types of biomedical data. Such rich data can be used to greatly improve health care. However, the development of a robust BC decision support system (BCDSS) that is driven by the available data remains a major challenge. The expanded utilization of BCDSS has been limited by the fact that current available systems are developed based on different data models and data taxonomies. In addition, the increasing availability of genetic data and the association between genotype and various diseases necessitates an integrated model that incorporates a comprehensive view of biomedical and clinical information. Such an integrated model would make it possible to develop a robust and standard BC information systems (BCIS). Standardized databases of BCIS would certainly make it much easier to take full advantage of BCDSS as well as other advances in all domains of biomedical research. This paper presents the framework for human BC data structures and an attempt to create a flexible data model that supports the notion of healthcare IT standards and accommodates the design/development of domain-specific BC databases.
Keywords :
data analysis; data models; decision making; decision support systems; genetics; health care; medical information systems; patient diagnosis; BC decision support system; BC institutions; BCDSS; BCIS; association; available systems; biomedical and clinical research domain; biomedical information; clinical data structures; clinical information; data analysis tools; data models; data taxonomies; data-driven decision making; data-intensive field; diagnostic equipment; diseases; domain-specific BC database design; domain-specific BC database development; flexible data model; genetic data; genotype; healthcare IT standards; human BC data structures; human biomedical data structures; integrated model; standard BC information systems; standardized databases; Bioinformatics; Data models; Databases; Diseases; Medical diagnostic imaging; Standards; Integrated data models; biomedical data; clinical data structure; clinical database; decision support systems; electronic medical records;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computational Advances in Bio and Medical Sciences (ICCABS), 2014 IEEE 4th International Conference on
Conference_Location :
Miami, FL
Print_ISBN :
978-1-4799-5786-6
Type :
conf
DOI :
10.1109/ICCABS.2014.6863910
Filename :
6863910
Link To Document :
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