Systems and Means of Informatics
2024, Volume 34, Issue 4, pp 59-72
COOPERATIVE SELF-CONFIGURING HYBRID INTELLIGENT SYSTEMS FOR PERSONALIZED DIAGNOSTICS AND PROGNOSIS IN MEDICINE: CONCEPTUAL IDEA, DEVELOPMENT APPROACH, AND PROBLEM DECOMPOSITION
- S. B. Rumovskaya
- F. N. Paramzin
Abstract
The clinical picture of polymorbid, polyetiological diseases (including acute pancreatitis) is diverse, unpredictable, and can intersect with many other diseases. This changes and complicates the process of personalized assessment (diagnostic and prognostic) of the state of a complex object in medicine (a patient) which entails serious errors and risks. It is necessary to support decision-making in medicine by artificial intelligence systems. The paper proposes cooperative selfconfiguring hybrid intelligent systems (using acute pancreatitis as an example) and also considers the results of reducing the problem of personalized assessment of the patient's condition and specification of tasks from the resulting decomposition.
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[+] About this article
Title
COOPERATIVE SELF-CONFIGURING HYBRID INTELLIGENT SYSTEMS FOR PERSONALIZED DIAGNOSTICS AND PROGNOSIS IN MEDICINE: CONCEPTUAL IDEA, DEVELOPMENT APPROACH, AND PROBLEM DECOMPOSITION
Journal
Systems and Means of Informatics
Volume 34, Issue 4, pp 59-72
Cover Date
2024-12-10
DOI
10.14357/08696527240405
Print ISSN
0869-6527
Publisher
Institute of Informatics Problems, Russian Academy of Sciences
Additional Links
Key words
hybrid intelligent decision support systems; problem-instrumental methodology; council; assessment of the severity and prognosis of the patient’s condition
Authors
S. B. Rumovskaya and F. N. Paramzin ,
Author Affiliations
Federal Research Center "Computer Science and Control", Russian Academy of Sciences, 44-2 Vavilov Str., Moscow 119333, Russian Federation
Central City Clinical Hospital, 3-5 Letnyaya Str., Kaliningrad 236005, Russian Federation
Immanuel Kant Baltic Federal University, 14 Nevskogo Str., Kaliningrad 236041, Russian Federation
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