Email this article Results of research work Russian society of oncomammologists “The use of artificial intelligence for early detection of breast cancer”
- Authors: Pavlova V.I.1, Belaya Y.A.2, Vorontsov A.Y.3, Prishchepov A.A.1, Knyazev S.M.2, Mikhaylov A.A.3, Kovaleva A.V.2, Arevshatyan E.G.3, Paltuev R.M.4, Chernaya A.V.4, Zakharova N.A.5
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Affiliations:
- Tyumen State Medical University, Ministry of Health of the Russia
- Khanty-Mansiysk Regional Clinical Hospital
- Nizhny Novgorod Regional Clinical Oncological Dispensary
- N.N. Petrov National Medical Research Oncology Center, Ministry of Health of Russia
- Luton and Dunstable University Hospital
- Issue: Vol 19, No 2 (2023)
- Pages: 54-60
- Section: MAMMOLOGY. ORIGINAL REPORTS
- Published: 05.08.2023
- URL: https://ojrs.abvpress.ru/ojrs/article/view/1102
- DOI: https://doi.org/10.17650/1994-4098-2023-19-2-54-60
- ID: 1102
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Abstract
Breast cancer is the most common cancer in women and one of the leading causes of death from cancer in Russia and most countries of the world. In countries with mammographic screening, there is a decrease in mortality from breast cancer. Introduction of mammographic image evaluation platforms into radiologist practice based on the work of artificial intelligence it allows not only to increase the coverage of the female population, but also to reduce the cost of screening, but it also increases the sensitivity and specificity of mammography as a method of breast cancer screening.
The article presents the results of a study on the evaluation of mammographic images in women who have passed a preventive study using an artificial intelligence program.
Within the framework of this project, mammographic images were analyzed using the service for viewing medical images “Celsus” in 8030 patients. The study assessed the age groups of 40-49 years, 50-59 years, 60 years and older. The average age of patients with suspected breast cancer was 54.8 years. Breast cancer was detected in 13 women (1.2 %), while the highest percentage of breast cancer was detected in the group with mammographic density D.
Keywords
About the authors
V. I. Pavlova
Tyumen State Medical University, Ministry of Health of the Russia
Author for correspondence.
Email: pavlova.valeria@mail.ru
ORCID iD: 0000-0002-0899-0809
Valeriya I. Pavlova.
54 Odesskaya St., Tyumen 625023
Russian FederationYu. A. Belaya
Khanty-Mansiysk Regional Clinical Hospital
Email: juliyabelaya86@gmail.com
Yuliya A. Belaya.
40 Kalinina St., Khanty-Mansiysk 628011
Russian FederationA. Yu. Vorontsov
Nizhny Novgorod Regional Clinical Oncological Dispensary
11/1 Delovaya St., Nizhny Novgorod 603093
Russian FederationA. A. Prishchepov
Tyumen State Medical University, Ministry of Health of the Russia
ORCID iD: 0000-0002-5639-7321
54 Odesskaya St., Tyumen 625023
Russian FederationS. M. Knyazev
Khanty-Mansiysk Regional Clinical Hospital
40 Kalinina St., Khanty-Mansiysk 628011
Russian FederationA. A. Mikhaylov
Nizhny Novgorod Regional Clinical Oncological Dispensary
11/1 Delovaya St., Nizhny Novgorod 603093
Russian FederationA. V. Kovaleva
Khanty-Mansiysk Regional Clinical Hospital
40 Kalinina St., Khanty-Mansiysk 628011
Russian FederationE. G. Arevshatyan
Nizhny Novgorod Regional Clinical Oncological Dispensary
11/1 Delovaya St., Nizhny Novgorod 603093
Russian FederationR. M. Paltuev
N.N. Petrov National Medical Research Oncology Center, Ministry of Health of Russia
ORCID iD: 0000-0002-0871-9453
68 Leningradskaya St., Pesochnyy Settlement, Saint Petersburg 197758
Russian FederationA. V. Chernaya
N.N. Petrov National Medical Research Oncology Center, Ministry of Health of Russia
ORCID iD: 0000-0002-7975-3165
68 Leningradskaya St., Pesochnyy Settlement, Saint Petersburg 197758
Russian FederationN. A. Zakharova
Luton and Dunstable University Hospital
Lewsey Road, Luton, LU4 0DZ
United KingdomReferences
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