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JOURNALS // Artificial Intelligence and Decision Making // Archive

Artificial Intelligence and Decision Making, 2022 Issue 2, Pages 3–16 (Mi iipr60)

This article is cited in 3 papers

Intelligent systems and robots

Intelligent system for predicting the feasibility of using computed tomography

O. P. Shesternikovaa, V. K. Finnb, K. A. Leskoc, L. V. Vinokurovac

a Central Scientific Research Institute of Organization and Informatization of Public Health, Moscow, Russia
b Federal Research Center "Computer Science and Control" of Russian Academy of Sciences, Moscow, Russia
c GBUZ Moscow Clinical Scientific Center named after Loginov MHD, Moscow, Russia

Abstract: The article describes principles of creating an intelligent system using JSM-method of automated research support (JSM-method ARS) to predict the necessity for computed tomography application. The procedures of JSM-research (one of the JSM-method ARS stages) designed to increase the reliability of the regularities obtained in the system are described. The obtained regularities and their expert ratings are given.

Keywords: data mining, intelligent data analysis, JSM-method, automated research support, computed tomography, pancreatic cancer, chronic pancreatitis, differential diagnosis.

DOI: 10.14357/20718594220201


 English version:
, 2023, 50:5, 464–474

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© Steklov Math. Inst. of RAS, 2026