Classification of melanonychia, Beau's lines, and nail clubbing based on nail images and transfer learning techniques
Yükleniyor...
Dosyalar
Tarih
2023
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Erişim Hakkı
info:eu-repo/semantics/openAccess
Özet
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.
Açıklama
Anahtar Kelimeler
Artificial intelligence, Transfer learning, Nail disease classification, Deep learning, Computer-assisted diagnosis
Kaynak
Peerj Computer Science
WoS Q Değeri
Q1
Scopus Q Değeri
Q1
Cilt
9
Sayı
Künye
Soğukkuyu, D. Y. C., & Ata, O. (2023). Classification of melanonychia, Beau’s lines, and nail clubbing based on nail images and transfer learning techniques. PeerJ Computer Science, 9, e1533.
