Evaluation of the effectiveness of the decision support algorithm for physicians in retinal dystrophy using machine learning methods
Электронный научный архив УРФУ
Информация об архиве | Просмотр оригинала| Поле | Значение | |
| Заглавие |
Evaluation of the effectiveness of the decision support algorithm for physicians in retinal dystrophy using machine learning methods
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| Автор |
Zhdanov, A. E.
Dolganov, A. Yu. Zanca, D. Borisov, V. I. Luchian, E. Dorosinsky, L. G. |
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| Тематика |
DECISION SUPPORT ALGORITHM
DECISION TREES ELECTROPHYSIOLOGICAL STUDY ELECTRORETINOGRAM ELECTRORETINOGRAPHY EPS ERG RETINAL DYSTROPHY WAVELET ANALYSIS WAVELET SCALOGRAM DECISION SUPPORT SYSTEMS DECISION TREES ELECTROPHYSIOLOGY LEARNING ALGORITHMS MACHINE LEARNING OPHTHALMOLOGY PEDIATRICS DECISION SUPPORT ALGORITHMS ELECTROPHYSIOLOGICAL STUDIES ELECTRORETINOGRAMS ELECTRORETINOGRAPHY EPS ERG MACHINE LEARNING METHODS RETINAL DYSTROPHY WAVELET SCALOGRAM WAVELET-ANALYSIS WAVELET ANALYSIS |
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| Описание |
Electroretinography is a method of electrophysiological testing, which allows diagnosing dis-eases associated with disorders of the vascular structures of the retina. The classical analysis of the electroretinogram is based on assessing four parameters of the amplitude-time representation and often needs to be specified further using alternative diagnostic methods. This study proposes the use of an original physician decision support algorithm for diagnosing retinal dystrophy. The proposed algorithm is based on machine learning methods and uses parameters extracted from the wavelet scalogram of pediatric and adult electroretinogram signals. The study also uses a labeled database of pediatric and adult electroretinogram signals recorded using a computerized electrophysiological workstation EP-1000 (Tomey GmbH) at the IRTC Eye Microsurgery Ekaterinburg Center. The scientific novelty of this study consists in the development of special mathematical and algorithmic software for analyzing a procedure for extracting wavelet scalogram parameters of the electroretinogram signal using the cwt function of the PyWT. The basis function is a Gaussian wavelet of order 8. Also, the scientific novelty includes the development of an algorithm for analyzing electroretinogram signals that implements the classification of adult (pediatric) electro-retinogram signals 19 (20) percent more accurately than classical analysis. © 2023, Institution of Russian Academy of Sciences. All rights reserved.
Ministry of Education and Science of the Russian Federation, Minobrnauka Acknowledgements: The research funding from the Ministry of Science and Higher Education of the Russian Federation (Ural Federal University Program of Development within the Priority-2030 Program) is gratefully acknowledged. |
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| Дата |
2024-04-05T16:15:47Z
2024-04-05T16:15:47Z 2023 |
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| Тип |
Article
Journal article (info:eu-repo/semantics/article) |info:eu-repo/semantics/publishedVersion |
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| Идентификатор |
Жданов, АЕ, Долганов, АЮ, Занка, Д, Борисов, ВИ, Лучиан, Е & Доросинский, ЛГ 2023, 'Оценка эффективности алгоритма поддержки принятия решения врачом при дистрофии сетчатки с использованием методов машинного обучения', Computer Optics, Том. 42, № 2, стр. 272-277. https://doi.org/10.18287/2412-6179-CO-1124
Жданов, А. Е., Долганов, А. Ю., Занка, Д., Борисов, В. И., Лучиан, Е., & Доросинский, Л. Г. (2023). Оценка эффективности алгоритма поддержки принятия решения врачом при дистрофии сетчатки с использованием методов машинного обучения. Computer Optics, 42(2), 272-277. https://doi.org/10.18287/2412-6179-CO-1124 0134-2452 Final All Open Access, Gold, Green https://www.scopus.com/inward/record.uri?eid=2-s2.0-85148454222&doi=10.18287%2f2412-6179-CO-1124&partnerID=40&md5=7ae075f3e730511e35571714e69e3166 https://computeroptics.ru/KO/PDF/KO47-2/470210.pdf http://elar.urfu.ru/handle/10995/130208 50281208 10.18287/2412-6179-CO-1124 85148454222 |
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| Язык |
ru
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| Права |
Open access (info:eu-repo/semantics/openAccess)
cc-by https://creativecommons.org/licenses/by/4.0/ |
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| Формат |
application/pdf
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| Издатель |
Institution of Russian Academy of Sciences
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| Источник |
Computer Optics
Computer Optics |
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