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dc.contributor.authorShchetinin, E. Yu.-
dc.contributor.authorTiutiunnik, A. A.-
dc.date.accessioned2025-04-21T12:12:43Z-
dc.date.available2025-04-21T12:12:43Z-
dc.date.issued2025-
dc.identifier.citationShchetinin, E.Yu. Coronary artery stenosis detection based on deep learning models / Shchetinin E.Yu., A.A. Tiutiunnik ; RUDN University, Moscow // Научный результат. Сер. Информационные технологии. - 2025. - Т.10, №1.-С. 58-65. - Doi: 10.18413/2518-1092-2025-10-1-0-6.ru
dc.identifier.urihttp://dspace.bsu.edu.ru/handle/123456789/64901-
dc.description.abstractThis article discusses popular deep learning-based stenosis detection models. The models differed in their basic neural network architecture and were pre-trained on publicly available data. A comparative analysis of the models is presented based on the main performance indicators: average accuracy (mAP), image processing time, and the number of model parametersru
dc.language.isoenru
dc.subjectmedicineru
dc.subjectmedical informaticsru
dc.subjectclinical cardiologyru
dc.subjectdeep learningru
dc.subjectcoronary artery stenosisru
dc.subjectneural networksru
dc.subjectX-ray coronary angiographyru
dc.titleCoronary artery stenosis detection based on deep learning modelsru
dc.typeArticleru
Appears in Collections:Т. 10, № 1

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