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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