ABSTRACTS OF ARTICLES OF THE JOURNAL "INFORMATION TECHNOLOGIES".
No. 2. Vol. 25. 2019

DOI: 10.17587/it.25.97-106

V. V. Gribova, D. Sc. (Technical Sciences), Deputy Director, Head of intelligent systems lab, gribova@iacp.dvo.ru, Ph. M. Moskalenko, Ph. D. (Technical Sciences), Senior Researcher in intelligent systems lab, philipmm@iacp.dvo.ru, Institute of Automation and Control Processes FEB RAS, Vladivostok, C. I. Shahgeldyan, D. Sc. (Technical Sciences), Head of information technologies institute, carinash@vvsu.ru, D. V. Gmar', Head of information technology center, dmitriy.gmar@vvsu.ru, Vladivostok State University of Economics and Service, Vladivostok, B. I. Geltser, D. Sc. (Medical Sciences), Head of clinical medicine department of Biomedicine school, boris.geltser@vvsu.ru, Far-Eastern State University, Vladivostok

A Concept for a Heterogeneous Biomedical Information Warehouse

One of the major obstacles of expanding research in the field of personified medicine is the lack of technology for storing, processing, analyzing and verifying of biomedical information. The paper proposed the concept of biomedical data and knowledge warehouse, which combines information from different sources of various nature. The architectural feature is the integration of primary clinical and statistical data, results of their processing and analysis, combination of the latter with known medical knowledge on diagnostics and disease treatment and their use in clinical medicine. Heterogeneous warehouse has a component distributed architecture and combines information (ontologies, data and knowledge bases) and software (system, specialized and applied) units. Ontologies are divided into three layers: infrastructure (meant for infrastructure support of the warehouse), information (support formation of data and knowledge components) and software (these ontologies set structures for software components). Data is divided into primary (received form outer sources — case records, formalized data of the medical organizations, medical statistics, monitoring logs) and secondary (acquired while data analysis by statistical methods, machine learning and artificial intelligence). Knowledge bases describe diagnostics, cures and pharmacotherapy, treatment assignment. Several information resources and software components are described (medical terminology and observations glossary, export/ import tool, clinical data preprocessing tool, statistics data preprocessing tool, specialized shell for decision support system development). To date, many software and information components of the warehouse have been developed and are being used, work continues on the creation of new components and the improvement of existing ones.
Keywords: heterogeneous repository of biomedical information, intelligent information systems, data analysis methods, ontologies, knowledge bases

P. 97–106

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