Abstract
In the paper a hierarchy of formalized models for data, information and knowledge representation in medical domain is proposed. The models allow solving problems of calculation, evaluation and analysis of complex indicators of patient’s organism state. The model hierarchy is composed of raw objective numerical data description, the description of the outputs of statistical and intelligent processing and analyses procedures. To build the model a set of transformations are defined according to JDL fusion model adapted for medical objective data. Models are implemented as a system of ontologies. Experimental research of the models and transformations was conducted on historical data of Almazov Medicine research center (Saint-Petersburg, Russia).
Keywords
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsReferences
Petlenko V.P., Popov A.S.: Philosophical problems of medicine (1978)
USA National Medical Library. https://www.nlm.nih.gov/
Neznanov, A.A., Starichkova, Y.V.: Development of classification of clinical diagnoses in medical information systems, Business Informatics (2015)
Neznanov, A.A.: Modern mathematical models of medical informatics: the statistics to mining (2016)
ICH. http://www.ich.org
CONSORT. http://www.consort-statement.org
Metathesaurus. http://www.nlm.nih.gov/research/umls/quickstart.html
SNOMED CT. http://www.ihtsdo.org/snomed-ct
Technical Implementation Guide. http://ihtsdo.org/fileadmin/user_upload/doc/en_us/tig.html
MedDRA. http://www.meddra.org
ICD10Data. http://www.icd10data.com
RxNorm. http://www.nlm.nih.gov/research/umls/rxnorm/index.html
Steinberg, A.N., Bowman, C.L., White, F.E.: Revisions to the JDL data fusion model. In: The Joint NATO/IRIS Conference, Quebec (1998)
Zhukova, N.A., Pankin, A.V.: Principles of managing the processing and analysis of multi-dimensional measurements in IGIS. In: Proceedings of the Information Technologies in Man-Agement, Saint-Petersburg, 9–11 October (2012)
Shanin Yu., N.: Postoperative intensive therapy (1978)
Mirkin, B.G., Kupershtok, B.L.: Amount of internal relations classification as an indicator of quality (1976)
Mandel ID.: Cluster analysis. Moscow, Finance and Statistics (1988)
Multivariate statistical analysis: Timashevicha, V.N. (ed.). Moscow, UNITY (1999)
Piatetsky-Shapiro, G.: From Data Mining to Knowledge Discovery in Databases (1996)
ISST. http://isst.ifmo.ru/en/
InterSystems Cache. http://www.intersystems.com/our-products/cache/cache-overview/
Witten, I.H., Frank, E., Hall, M.A.: Data Mining: Practical Machine Learning Tools and Techniques (2011)
Metaphacts. http://www.metaphacts.com/
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2016 Springer International Publishing Switzerland
About this paper
Cite this paper
Lushnov, M., Kudashov, V., Vodyaho, A., Lapaev, M., Zhukova, N., Korobov, D. (2016). Medical Knowledge Representation for Evaluation of Patient’s State Using Complex Indicators. In: Ngonga Ngomo, AC., Křemen, P. (eds) Knowledge Engineering and Semantic Web. KESW 2016. Communications in Computer and Information Science, vol 649. Springer, Cham. https://doi.org/10.1007/978-3-319-45880-9_26
Download citation
DOI: https://doi.org/10.1007/978-3-319-45880-9_26
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-45879-3
Online ISBN: 978-3-319-45880-9
eBook Packages: Computer ScienceComputer Science (R0)