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JOURNALS // Sistemy i Sredstva Informatiki [Systems and Means of Informatics] // Archive

Sistemy i Sredstva Inform., 2024 Volume 34, Issue 4, Pages 59–72 (Mi ssi956)

Cooperative self-configuring hybrid intelligent systems for personalized diagnostics and prognosis in medicine: conceptual idea, development approach, and problem decomposition

S. B. Rumovskayaa, F. N. Paramzinbc

a Federal Research Center "Computer Science and Control" of the Russian Academy of Sciences, 44-2 Vavilov Str., Moscow 119133, Russian Federation
b Central City Clinical Hospital, 3-5 Letnyaya Str., Kaliningrad 236005, Russian Federation
c Immanuel Kant Baltic Federal University, 14 Nevskogo Str., Kaliningrad 236041, Russian Federation

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 self-configuring 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.

Keywords: hybrid intelligent decision support systems, problem-instrumental methodology, council, assessment of the severity and prognosis of the patient's condition.

Received: 29.08.2024

DOI: 10.14357/08696527240405



© Steklov Math. Inst. of RAS, 2025