Geodesic
Application of the machine learning method to solve
News of the Kabardin-Balkar scientific center of RAS, no. 6 (2021), pp. 58-65.

Voir la notice de l'article provenant de la source Math-Net.Ru

The paper solves the problem of creating a software package for computer diagnostics of gastritis. Patient examination indicators and their diagnoses are used as input data. To successfully solve the task, a logical approach to data analysis is being developed, which allows us to find the patterns necessary for qualitative diagnostics. These patterns are identified based on the data provided by specialists and include the results of patient examinations and existing medical practice experience in diagnosis. Systems of multivalued predicate logic are used for expressive representation of data. An algorithm is proposed that implements and simplifies the approaches under consideration. As a result, the developed software package selects the most suitable types of the disease with a predetermined accuracy according to the data of the diagnosis of patients. If it is not possible to make a diagnosis with a desired accuracy based on the results of the examination, then either the accuracy of the solution should be changed, or the patient is proposed to undergo an additional examination.
Keywords: : diagnostics, knowledge base, algorithm, axioms.
Mots-clés : clauses 
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L. A. Lyutikova; E. V. Shmatova. Application of the machine learning method to solve. News of the Kabardin-Balkar scientific center of RAS, no. 6 (2021), pp. 58-65. http://geodesic.mathdoc.fr/item/IZKAB_2021_6_a4/

[1] Yu. I. Zhuravlev, “On an algebraic approach to solving problems of recognition or classification”, Problems of Cybernetics, 33 (1978), 5–68 (In Russian) | Zbl

[2] Z. M. Shibzukhov, “Correct Aggregation Operations with Algorithms”, Pattern Recognition and Image Analysis, 24:3 (2014), 377–382 | DOI

[3] Ashley I. Naimi, B. Laura, “Balzer Stacked generalization: an introduction to super learning”, European Journal of Epidemiology, 2018, no. 33, 459–464

[4] R. Mesiar, M. Komornikova, A. Kolesarova, T. Calvo, Fuzzy Aggregation Functions: A revision. Sets and Their Extensions: Representation, Aggregation and Models, Springer-Verlag, Berlin, 2008

[5] Fan Yang, Zhilin Yang, William W., “Cohen Differentiable Learning of Logical Rules for Knowledge Base Reasoning”, Advances in Neural Information Processing Systems, 2017 (2017), 2320–2329

[6] P. Flach, Machine Learning: The Art and Science of Algorithms that Make Sense of Data, Cambridge University Press, 2012, 396 pp.

[7] Rahman Akhlaqur, Tasnim Sumaira, “Ensemble Classifiers and Their Applications: A Review”, International Journal of Computer Trends and Technology, 10:1 (2014), 31–35 | DOI

[8] L. A. Lyutikova, E. V. Shmatova, “Application of Variable-Valued Logic to Correct Pattern Recognition Algorithms”, Advances in Intelligent Systems and Computing, 948 (2020), 308–314 | DOI

[9] Christopher J. C. Burges, “A Tutorial on Support Vector Machines for Pattern Recognition”, Data Mining and Knowledge Discovery, v. 2, 1998, 121–167

[10] L. A. Lyutikova, “Use of logic with a variable valency under knowledge bases modeling”, CSR-2006