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Classification of melanonychia, Beau’s lines, and nail clubbing based on nail images and transfer learning techniques
BACKGROUND: Nail diseases are malformations that appear on the nail plate and are classified according to their own signs and symptoms that may be related to other medical conditions. Although most nail diseases have distinct symptoms, making a differential diagnosis of nail problems can be challeng...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
PeerJ Inc.
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10495933/ https://www.ncbi.nlm.nih.gov/pubmed/37705653 http://dx.doi.org/10.7717/peerj-cs.1533 |
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author | Coşar Soğukkuyu, Derya Yeliz Ata, Oğuz |
author_facet | Coşar Soğukkuyu, Derya Yeliz Ata, Oğuz |
author_sort | Coşar Soğukkuyu, Derya Yeliz |
collection | PubMed |
description | BACKGROUND: Nail diseases are malformations that appear on the nail plate and are classified according to their own signs and symptoms that may be related to other medical conditions. Although most nail diseases have distinct symptoms, making a differential diagnosis of nail problems can be challenging for medical experts. METHOD: One early diagnosis method for any dermatological disease is designing an image analysis system based on artificial intelligence (AI) techniques. This article implemented a novel model using a publicly available nail disease dataset to determine the occurrence of three common types of nail diseases. Two classification models based on transfer learning using visual geometry group (VGGNet) were utilized to detect and classify nail diseases from images. RESULT AND FINDING: The experimental design results showed good accuracy: VGG16 had a score of 94% accuracy and VGG19 had a 93% accuracy rate. These findings suggest that computer-aided diagnostic systems based on transfer learning can be used to identify multiple-lesion nail diseases. |
format | Online Article Text |
id | pubmed-10495933 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | PeerJ Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-104959332023-09-13 Classification of melanonychia, Beau’s lines, and nail clubbing based on nail images and transfer learning techniques Coşar Soğukkuyu, Derya Yeliz Ata, Oğuz PeerJ Comput Sci Bioinformatics BACKGROUND: Nail diseases are malformations that appear on the nail plate and are classified according to their own signs and symptoms that may be related to other medical conditions. Although most nail diseases have distinct symptoms, making a differential diagnosis of nail problems can be challenging for medical experts. METHOD: One early diagnosis method for any dermatological disease is designing an image analysis system based on artificial intelligence (AI) techniques. This article implemented a novel model using a publicly available nail disease dataset to determine the occurrence of three common types of nail diseases. Two classification models based on transfer learning using visual geometry group (VGGNet) were utilized to detect and classify nail diseases from images. RESULT AND FINDING: The experimental design results showed good accuracy: VGG16 had a score of 94% accuracy and VGG19 had a 93% accuracy rate. These findings suggest that computer-aided diagnostic systems based on transfer learning can be used to identify multiple-lesion nail diseases. PeerJ Inc. 2023-08-24 /pmc/articles/PMC10495933/ /pubmed/37705653 http://dx.doi.org/10.7717/peerj-cs.1533 Text en © 2023 Coşar Soğukkuyu and Ata https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ Computer Science) and either DOI or URL of the article must be cited. |
spellingShingle | Bioinformatics Coşar Soğukkuyu, Derya Yeliz Ata, Oğuz Classification of melanonychia, Beau’s lines, and nail clubbing based on nail images and transfer learning techniques |
title | Classification of melanonychia, Beau’s lines, and nail clubbing based on nail images and transfer learning techniques |
title_full | Classification of melanonychia, Beau’s lines, and nail clubbing based on nail images and transfer learning techniques |
title_fullStr | Classification of melanonychia, Beau’s lines, and nail clubbing based on nail images and transfer learning techniques |
title_full_unstemmed | Classification of melanonychia, Beau’s lines, and nail clubbing based on nail images and transfer learning techniques |
title_short | Classification of melanonychia, Beau’s lines, and nail clubbing based on nail images and transfer learning techniques |
title_sort | classification of melanonychia, beau’s lines, and nail clubbing based on nail images and transfer learning techniques |
topic | Bioinformatics |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10495933/ https://www.ncbi.nlm.nih.gov/pubmed/37705653 http://dx.doi.org/10.7717/peerj-cs.1533 |
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