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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.
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
Linking options:
https://www.mathnet.ru/eng/iipr60 https://www.mathnet.ru/eng/iipr/y2022/i2/p3
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Statistics & downloads: |
Abstract page: | 17 | Full-text PDF : | 12 |
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