admin

Issue 2 (192), article 5

DOI:https://doi.org/10.15407/kvt192.02.072

Kibern. vyčisl. teh., 2018, Issue 2 (192), pp.

Rysovana L.M.1,
Assistant,
Department of Medical and Biological Physics and Medical Informatics
e-mail: rluba_24@ukr.net
Vуsotska O.V.2,
Dr (Engineering), Professor,
Professor of the Department of Information Control Systems
e-mail: evisotska@ukr.net
1Kharkov National Medical University,
Nauky ave., 4, 61022, Kharkiv, Ukraine
2Kharkov National University of Radio Electronics,
Nauky ave., 14, 61166, Kharkiv, Ukraine

INFORMATION SYSTEM OF DETECTION OF EMOTIONAL AND COGNITIVE DISORDERS IN PATIENTS WITH DISCIRCULATORY ENCEPHALOPATHY

Introduction. In modern conditions, there are topical issues of studying the mechanisms of formation and specificity of clinical manifestations of discirculatory encephalopathy in the able-bodied population. A large number of interrelated indicators that characterize emotional and cognitive disorders, the analysis of which requires the use of mathematical methods and software, determined the need to develop an information system for the detection of emotional and cognitive disorders in patients with discirculatory encephalopathy.
The purpose of the article is to develop a medical information system for the detection of emotional and cognitive disorders in patients with discirculatory encephalopathy, which increases the accuracy of diagnosis.
Materials and methods. The article uses mathematical statistics methods for processing diagnostic information; methods of mathematical modeling for constructing mathematical models for detecting the likelihood of emotional disorders and identifying and determining the severity of cognitive disorders in patients with discirculatory encephalopathy; methodical bases of construction of information technologies in medicine at construction of information system of revealing emotional and cognitive disorders in patients with discirculatory encephalopathy.
Results. During the writing of the article, a method was developed for detecting emotional and cognitive disorders in patients with discirculatory encephalopathy, including the definition of the likelihood of emotional disorders, the exposure vector for psychocorrection, the detection of cognitive disorders and determining their severity, and predicting the further development of cognitive disorders. A structural diagram of the medical information system “СognitiveDE” has been developed, which determines the composition and purpose of its main modules, and has allowed to develop a methodological basis for describing the interaction of the elements of the biological and technical subsystems. The software of the medical information system “СognitiveDE” was verified, which showed the compliance of the results of the individual stages of the system development with the requirements and restrictions formulated for them.
Conclusions. Using the developed method for detecting emotional and cognitive disorders in patients with discirculatory encephalopathy, based on developed mathematical models for determining the likelihood of emotional disorders and determining the severity of cognitive disorders, allows correctly diagnosing emotional and cognitive disorders.
The presented medical information system can be used by doctors of the neurological and psychiatric departments and medical psychologists to improve the accuracy and reduce the time of diagnosis of emotional and cognitive disorders.

Keywords: medical information system, assessment method, cognitive and emotional disorders, discirculatory encephalopathy.

Download full text!

REFERENCES

  1. Vysotskaya E.V., Kоzhina А.М., Risovanaya L.M., Chaika H.E. Application of discriminant analysis for the classification of cognitive disorders in patients with discirculatory encephalopathy. Information processing system, 2013, Vol. 9, pp. 189–193. (In Russian).
  2. Kоzhina А.М., Grigorova І.А., Korosty V.І. and others. Organic mental disorders due to somatic diseases: cognitive and emotional disorders. Kharkov: Ukraine Rarities, 2012, 120 p. (In Ukrainian).
  3. Aleksandrovsky Y.A., Shchukin B.P. Psychological disorders during and after natural disasters and disasters. Journal of Neuropathology and Psychiatry, 1991, Vol. 5, pp. 39–43. (In Russian).
  4. Bleicher V.M., Krook I.V., Bokov S.N. Clinical Pathopsychology. Moskow, 2002,
    511 pp. (In Russian).
  5. Miroshnikov S.A. Expert system Longitude. The experimental and diagnostic complex (EDC). SPb: Lema, 2010, 196 pp. (In Russian)
  6. Altamirov S.A. Application of information technology in the activities of a psychiatrist. Young Scientis, 2016, Vol. 29, pp. 200–203. (In Russian).
  7. Aimedica. General information. http://aimedica.ru/info.jsp. (In Russian).
  8. Kan L.V., Kuznetsova Y.M., Chudova N.V. Expert systems in the field of psychodiagnostics. Artificial Intelligence and Decision Making, 2010, Vol. 2, pp. 26–35. (In Russian).
  9. Rysovana L., Vysotska O., Porvan A., Alekseenko R. Family Crisis Investigation on the Basis of Regression Analysis. The problems of empirical research in psychology and humanities: Roland Barthes VIII International Scientific Conference. Europejskie Studia Humanistyczne: państwo i społeczeństwo. Krakow, 2016, Vol. 2, p. 83–91.
  10. Nechaeva G.I., Achmedov V.A., Bereznikov A.V. and others. Methodical approaches to the expert evaluation of the quality of therapeutic care for chronic cholecystitis. Therapeutic archive, 2010, Vol. 1, pp. 12–15. (In Russian).
  11. Watson A., McCabe T. Structured Testing: A Testing Methodology Using the Cyclomatic Complexity Metric. URL: http://www.mccabe.com/pdf/mccabe-nist235r.pdf. (Last accessed: 10.11.2017) 1996.

Received 26.02.2018