Development of automated methods for reducing the risk of critical conditions, based on the analysis of medical records
Author Affiliations1Novosibirsk National Research State University, 630090, Novosibirsk, Pirogov str., 2
2Novosibirsk National Research State University, 630090, Novosibirsk, Pirogov str., 2; Sobolev Institute of Mathematics of SB RAS, 630090, Novosibirsk, Koptyug av., 4
3Novosibirsk National Research State University, 630090, Novosibirsk, Pirogov str., 2
Abstract
This paper describes the methods of development of ontologies and ontological modes in medicine. We present four-level structure of knowledge representation. Using the basics of ontological methods of presenting knowledge, we developed algorithms to prevent risks of critical conditions and complications. The work is based on the model-theoretic approach to represent medical knowledge, which is shown through partial atomic diagrams of algebraic systems and of a patients’ cases data via Boolean-valued models. This data helped to develop ontology and ontological models of the «spinal deformity and spinal degenerative disease». The ontology model contains: a) general knowledge that is applicable for all patients, b) data on specific patients, and c) estimated knowledge that help doctors make recommendations. Estimated knowledge is a set of hypothetical possibilities that could lead to a patient’s critical condition or complications. We also developed an algorithm generating the estimated (fuzzy) knowledge based on the analysis of medical records. A software system generating recommendations to help prevent and reduce the risk of a patient’s critical condition (life threatening) was implemented. The results used in the study are from data of patients with spinal deformity or spinal degenerative diseases.
Key words
References
- Abas H., Yusof M., Noah S. The application of ontology in a clinical decision support system for acute postoperative pain management // STAIR: Proc. Int. Conf. Semantic Technology and Information Retrieval. Putrajaya, 2011. 106–112.
- Artemyeva I.L. Multilevel models of complex structured subject domains and their use in the development of the systems based on knowledge: abstract of thesis … doctor of technical sciences. Vladivostok, 2008. [In Russian].
- Chernyakhovskaya M.Yu. Formation of observation database on the basis of medicine ontology // Informatika i sistemy upravleniya = Information science and control systems. 2009. (4). 198–200. [In Russian].
- Clinical Decision Support Systems / Ed. Eta S. Berner. N. Y.: Springer, 2007.
- Denysenko S.V. Diagnosis and prognosis of states in invitro fertilization based on the ontology knowledge // Zaporozhskiy meditinskiy zhurnal = Zaporozhye medical journal. 2014. 2. 137–140. [In Russian].
- FAERS Reporting by Patient Outcomes by Year // U.S. Food and Drug Administration. URL: http://www.fda.gov/Drugs/GuidanceComplianceRegulatoryInformation/Surveillance/AdverseDrugEffects/ucm070461.htm (Accessed: 15.09.2015).
- Gribova V.V., Okun D.B., Chernyakhovskaya M.Yu. Ontology and ontology model of «Medication treatment» domain // Informatika i sistemy upravleniya = Information science and control systems. 2015. (2). 70–79. [In Russian].
- Gribova V.V., Petryaeva M.V., Fedorischev L.A. Formalization of examination method in ophthalmology for computer diagnostic simulators // High Technologies, Basic and Applied Researches in Physiology and Medicine: Abstr. III Int. Conf. St. Petersburg, 2012. 2. 191–195. [In Russian].
- Jeffery R., Iserman E., Haynes R. Can computerized clinical decision support systems improve diabetes management? A systematic review and meta-analysis // Diabet. Med. 2013. 30. (6). 739–745.
- Jia P., Zhang P., Li H. et al. Literature review on clinical decision support system reducing medical error // J. Evid. Based Med. 2014. 7. (3). 219–226.
- Kleschev A.S., Moskalenko F.M. Chernyakhovskaya M.Yu. Ontology model of Medical diagnostics» domain. Part 1. Informal description and definition of basic terms // Nauchno-tekhnicheskaya informatsiya. Seriya 2 = Automatic Documentation and Mathematical Linguistics. Series 2. 2005. (12). 1–7. [In Russian].
- Kleschev A.S., Moskalenko F.M. Chernyakhovskaya M.Yu. Ontology model of «Medical diagnostics» domain. Part 2. Formal description of causal links, reasons of feature values and reasons of diseases // Nauchno-tehnicheskaya informatsiya. Seriya 2 = Automatic Documentation and Mathematical Linguistics. Series 2. 2006. (2). 19–30. [In Russian].
- Kleschev A.S., Shalfeyeva E.A. System analysis contents for intelligent activity automation at branch level // OSTIS-2014: Abstr. Int. conf. Minsk, 2014. 285–290.
- Makhasoeva O.G., Palchunov D.E. Semi-automatic methods of construction of the atomic diagrams from natural language texts // Vestnik Novosibirskogo gosudartsvennogo universiteta. Seriya: Informatsionnye tekhnologii = Novosibirsk State University Journal of Information Technologies. 2014. 12. (2). 64–73. [In Russian].
- Mickan S., Tilson J., Atherton H. et al. Evidence of effectiveness of health care professionals using handheld computers: A scoping review of systematic reviews // J. Med. Internet Res. 2013. 15. (10). e212.
- Moskalenko F.M. Methods for solving the problem of medical diagnostics on the basis of a mathematical model of the subject domain: abstract of thesis … candidate of technical sciences. Vladivostok, 2010. [In Russian].
- Nuckols T., Smith-Spangler C., Morton S. et al. The effectiveness of computerized order entry at reducing preventable adverse drug events and medication errors in hospital settings: a systematic review and meta-analysis // Syst. Rev. 2014. 3. (1). ID 56.
- Palchunov D.E. Knowledge search and production: creation of new knowledge on the basis of natural language text analysis // Filosofiya nauki = Philosophy of Science. 2009. (4). 70–90. [In Russian].
- Palchunov D.E. Solution for Information Retrieval Problem Based on Ontologies // Biznes-informatika = Business informatics. 2008. (1). 3–13. [In Russian].
- Palchunov D.E. Virtual catalogue: the ontologybased technology for information retrieval // Knowledge Processing and Data Analysis: Coll. Sci. Art. Eds. K. Wolff, D. Palchunov, N. Zagoruiko, U. Andelfinger. Berlin; Heidelberg: Springer-Verlag, 2011. 164–183.
- Palchunov D.E., Stepanov P.A. Use of model-theoretic methods of extraction of ontological knowledge in the domain of information security // Programmnaya inzheneriya = Program engineering. 2013. (11). 8–16. [In Russian].
- Palchunov D.E., Yakhyaeva G.E. Fuzzy logics and fuzzy model theory // Algebra Logic. 2015. 54. (1). 74–80.
- Palchunov D.E., Yakhyaeva G.E., Hamutskaya A.A. Software system RiskPanel for management of information risks // Programmnaya inzheneriya = Program engineering. 2011. (7). 29–36.
- Patent N 2014619198 RF. Software system for building atomic diagram of model from natural language texts / Makhasoyeva O.G., Palchunov D.E.; published 11.07.2014.
- Phalakornkule K., Jones J., Finnell J. Ontological model for CDSS in knee injury management // Universal Access in Human-Computer Interaction. Applications and Services for Quality of Life: Coll. Sci. Art. Eds. C. Stephanidis, M. Antona. Berlin; Heidelberg: Springer-Verlag, 2013. 526–535.
- Seo D., Jung H., Sung W. et al. Development of Korean spine database and ontology for realizing e-Spine // Cluster Comput. 2014. 17. (3). 1069–1080.
About Authors (Correspondence):
Naydanov Ch.A. – postgraduate student, e-mail: naydanov.fit@yandex.ru
Palchunov D.E. – doctor of physical mathematical sciences, leading researcher, e-mail: palch@math.nsc.ru
Sazonova P.A. – master student, e-mail: psazonova@gmail.com
Full Text
Received: 22/03/2016
Accepted: 02/01/1970