Cloud-Based Service for Recognizing Pigmented Skin Lesions Using a Multimodal Neural Network System

Skin cancer is the most common cancer in humans today and is usually caused by exposure to ultraviolet radiation. There are many diagnostic methods for visual analysis of pigmented neoplasms. However, most of these methods are subjective and largely dependent on the experience of the clinician. To m...

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Hoofdauteurs:	Lyakhova, U. A., Ляхова, У. А., Bondarenko, D. N., Бондаренко, Д. Н., Boyarskaya, E. E., Боярская, Э. Е., Nagornov, N. N., Нагорнов, Н. Н.
Formaat:	Статья
Taal:	English
Gepubliceerd in:	2023
Onderwerpen:	Heterogeneous data Skin cancer Cloud-based system Melanoma Multimodal neural networks Pigmented skin lesions
Online toegang:	https://dspace.ncfu.ru/handle/20.500.12258/25248
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id	ir-20.500.12258-25248
record_format	dspace
spelling	ir-20.500.12258-252482023-09-08T09:38:45Z Cloud-Based Service for Recognizing Pigmented Skin Lesions Using a Multimodal Neural Network System Lyakhova, U. A. Ляхова, У. А. Bondarenko, D. N. Бондаренко, Д. Н. Boyarskaya, E. E. Боярская, Э. Е. Nagornov, N. N. Нагорнов, Н. Н. Heterogeneous data Skin cancer Cloud-based system Melanoma Multimodal neural networks Pigmented skin lesions Skin cancer is the most common cancer in humans today and is usually caused by exposure to ultraviolet radiation. There are many diagnostic methods for visual analysis of pigmented neoplasms. However, most of these methods are subjective and largely dependent on the experience of the clinician. To minimize the influence of the human factor, it is proposed to introduce artificial intelligence technologies that have made it possible to reach new heights in terms of the accuracy of classifying medical data, including in the field of dermatology. Artificial intelligence technologies can equal and even surpass the capabilities of an dermatologists in terms of the accuracy of visual diagnostics. The article proposes a web application based on a multimodal neural network system for recognizing pigmented skin lesions as an additional auxiliary tool for oncologist. The system combines and analyzes heterogeneous dermatological data, which are images of pigmented neoplasms and such statistical information about the patient as age, gender, and localization of pigmented skin lesions. The recognition accuracy of the proposed web application was 85.65%. The use of the proposed web application as an auxiliary diagnostic method will expand the possibilities of early detection of skin cancer and minimize the impact of the human factor. 2023-09-08T09:35:19Z 2023-09-08T09:35:19Z 2023 Статья Lyakhova, U.A., Bondarenko, D.N., Boyarskaya, E.E., Nagornov, N.N. Cloud-Based Service for Recognizing Pigmented Skin Lesions Using a Multimodal Neural Network System // Lecture Notes in Networks and Systems. - 2023. - 702 LNNS, pp. 401-409. - DOI: 10.1007/978-3-031-34127-4_39 http://hdl.handle.net/20.500.12258/25248 en Lecture Notes in Networks and Systems application/pdf
institution	СКФУ
collection	Репозиторий
language	English
topic	Heterogeneous data Skin cancer Cloud-based system Melanoma Multimodal neural networks Pigmented skin lesions
spellingShingle	Heterogeneous data Skin cancer Cloud-based system Melanoma Multimodal neural networks Pigmented skin lesions Lyakhova, U. A. Ляхова, У. А. Bondarenko, D. N. Бондаренко, Д. Н. Boyarskaya, E. E. Боярская, Э. Е. Nagornov, N. N. Нагорнов, Н. Н. Cloud-Based Service for Recognizing Pigmented Skin Lesions Using a Multimodal Neural Network System
description	Skin cancer is the most common cancer in humans today and is usually caused by exposure to ultraviolet radiation. There are many diagnostic methods for visual analysis of pigmented neoplasms. However, most of these methods are subjective and largely dependent on the experience of the clinician. To minimize the influence of the human factor, it is proposed to introduce artificial intelligence technologies that have made it possible to reach new heights in terms of the accuracy of classifying medical data, including in the field of dermatology. Artificial intelligence technologies can equal and even surpass the capabilities of an dermatologists in terms of the accuracy of visual diagnostics. The article proposes a web application based on a multimodal neural network system for recognizing pigmented skin lesions as an additional auxiliary tool for oncologist. The system combines and analyzes heterogeneous dermatological data, which are images of pigmented neoplasms and such statistical information about the patient as age, gender, and localization of pigmented skin lesions. The recognition accuracy of the proposed web application was 85.65%. The use of the proposed web application as an auxiliary diagnostic method will expand the possibilities of early detection of skin cancer and minimize the impact of the human factor.
format	Статья
author	Lyakhova, U. A. Ляхова, У. А. Bondarenko, D. N. Бондаренко, Д. Н. Boyarskaya, E. E. Боярская, Э. Е. Nagornov, N. N. Нагорнов, Н. Н.
author_facet	Lyakhova, U. A. Ляхова, У. А. Bondarenko, D. N. Бондаренко, Д. Н. Boyarskaya, E. E. Боярская, Э. Е. Nagornov, N. N. Нагорнов, Н. Н.
author_sort	Lyakhova, U. A.
title	Cloud-Based Service for Recognizing Pigmented Skin Lesions Using a Multimodal Neural Network System
title_short	Cloud-Based Service for Recognizing Pigmented Skin Lesions Using a Multimodal Neural Network System
title_full	Cloud-Based Service for Recognizing Pigmented Skin Lesions Using a Multimodal Neural Network System
title_fullStr	Cloud-Based Service for Recognizing Pigmented Skin Lesions Using a Multimodal Neural Network System
title_full_unstemmed	Cloud-Based Service for Recognizing Pigmented Skin Lesions Using a Multimodal Neural Network System
title_sort	cloud-based service for recognizing pigmented skin lesions using a multimodal neural network system
publishDate	2023
url	https://dspace.ncfu.ru/handle/20.500.12258/25248
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Cloud-Based Service for Recognizing Pigmented Skin Lesions Using a Multimodal Neural Network System

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