Artificial Intelligence and Decision Making
RUS  ENG    JOURNALS   PEOPLE   ORGANISATIONS   CONFERENCES   SEMINARS   VIDEO LIBRARY   PACKAGE AMSBIB  
General information
Latest issue
Archive
Guidelines for authors

Search papers
Search references

RSS
Latest issue
Current issues
Archive issues
What is RSS



Artificial Intelligence and Decision Making:
Year:
Volume:
Issue:
Page:
Find






Personal entry:
Login:
Password:
Save password
Enter
Forgotten password?
Register


Artificial Intelligence and Decision Making, 2022, Issue 2, Pages 3–16
DOI: https://doi.org/10.14357/20718594220201
(Mi iipr60)
 

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.
English version:
Scientific and Technical Information Processing, 2023, Volume 50, Issue 5, Pages 464–474
DOI: https://doi.org/10.3103/S0147688223050131
Bibliographic databases:
Document Type: Article
Language: Russian
Citation: O. P. Shesternikova, V. K. Finn, K. A. Lesko, L. V. Vinokurova, “Intelligent system for predicting the feasibility of using computed tomography”, Artificial Intelligence and Decision Making, 2022, no. 2, 3–16; Scientific and Technical Information Processing, 50:5 (2023), 464–474
Citation in format AMSBIB
\Bibitem{SheFinLes22}
\by O.~P.~Shesternikova, V.~K.~Finn, K.~A.~Lesko, L.~V.~Vinokurova
\paper Intelligent system for predicting the feasibility of using computed tomography
\jour Artificial Intelligence and Decision Making
\yr 2022
\issue 2
\pages 3--16
\mathnet{http://mi.mathnet.ru/iipr60}
\crossref{https://doi.org/10.14357/20718594220201}
\elib{https://elibrary.ru/item.asp?id=48707180}
\transl
\jour Scientific and Technical Information Processing
\yr 2023
\vol 50
\issue 5
\pages 464--474
\crossref{https://doi.org/10.3103/S0147688223050131}
Linking options:
  • https://www.mathnet.ru/eng/iipr60
  • https://www.mathnet.ru/eng/iipr/y2022/i2/p3
  • Citing articles in Google Scholar: Russian citations, English citations
    Related articles in Google Scholar: Russian articles, English articles
    Artificial Intelligence and Decision Making
    Statistics & downloads:
    Abstract page:17
    Full-text PDF :12
     
      Contact us:
     Terms of Use  Registration to the website  Logotypes © Steklov Mathematical Institute RAS, 2024