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Doklady Rossijskoj Akademii Nauk. Mathematika, Informatika, Processy Upravlenia, 2023, Volume 514, Number 2, Pages 20–27
DOI: https://doi.org/10.31857/S2686954323601367 (Mi danma447) 		 
SPECIAL ISSUE: ARTIFICIAL INTELLIGENCE AND MACHINE LEARNING TECHNOLOGIES

Probability calibration on the example of improving early cancer detection: a fuzzy set theory approach

O. A. Filimonova, A. G. Ovsyannikov, N. V. Biryukova

I. M. Sechenov First Moscow State Medical University, Resource Center "Medical Sechenov Preuniversary", Moscow, Russian Federation
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DOI: https://doi.org/10.31857/S2686954323601367
Abstract: Cancer is the leading cause of death before the age of 70 years. Cancer mortality is reduced by early detection. To improve the early diagnosis of cancer, we propose a novel probability calibration method based on a fuzzy set theory. Our model for binary classification was tested on the detection of female breast cancer and lung cancer. The first case is complicated by a small data set problem, while the second – by highly imbalanced data. In both cases, our probability calibration method improved Log Loss (the best result is improved on 48.86%), Brier score (the best result is improved on 13.24%), and the area under the PR curve (the best result is improved on 13.94%). The application area of our algorithm can be extended to any progressive diseases and events without a clearly defined boundary.
Keywords: probability calibration, fuzzy set theory, binary classification, early diagnosis of diseases.
Presented: A. I. Avetisyan
Received: 29.08.2023
Revised: 06.09.2023
Accepted: 15.10.2023
English version:
Doklady Mathematics, 2023, Volume 108, Issue suppl. 2, Pages S179–S185
DOI: https://doi.org/10.1134/S106456242370103X
Bibliographic databases:
Document Type: Article
UDC: 004.8
Language: Russian
Citation: O. A. Filimonova, A. G. Ovsyannikov, N. V. Biryukova, “Probability calibration on the example of improving early cancer detection: a fuzzy set theory approach”, Dokl. RAN. Math. Inf. Proc. Upr., 514:2 (2023), 20–27; Dokl. Math., 108:suppl. 2 (2023), S179–S185
Citation in format AMSBIB
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\by O.~A.~Filimonova, A.~G.~Ovsyannikov, N.~V.~Biryukova
\paper Probability calibration on the example of improving early cancer detection: a fuzzy set theory approach
\jour Dokl. RAN. Math. Inf. Proc. Upr.
\yr 2023
\vol 514
\issue 2
\pages 20--27
\mathnet{http://mi.mathnet.ru/danma447}
\crossref{https://doi.org/10.31857/S2686954323601367}
\elib{https://elibrary.ru/item.asp?id=56717703}
\transl
\jour Dokl. Math.
\yr 2023
\vol 108
\issue suppl. 2
\pages S179--S185
\crossref{https://doi.org/10.1134/S106456242370103X}
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