DETECTION OF NAIL DISEASES USING ENSEMBLE MODEL BASED ON MAJORITY VOTING

Senar Ali Yamaç; Orhun Kuyucuoğlu; Şeyma Begüm Köseoğlu; Sezer Ulukaya

doi:10.17780/ksujes.1224006

TR EN

ÇOĞUNLUK OYUNA DAYALI TOPLULUK MODELİ İLE TIRNAK HASTALIKLARININ TESPİTİ

Öz

Tırnak hastalıkları, insanın yaşam kalitesini ciddi şekilde etkileyebilen bozukluklardır. Gelişen hesaplamalı yöntemler ve teknoloji ile tırnaktaki anomaliler hızlı ve girişimsiz bir şekilde tespit edilebilmektedir. Bu çalışma, farklı derin öğrenme ağlarının sonuçlarını topluluk öğrenme yöntemiyle birleştirerek daha iyi performans sağlayan bir model önermektedir. 7 farklı derin öğrenme mimarisinin performansı, 17 hastalık sınıfı içeren bir veritabanı kullanılarak incelenmiştir. Önerilen yöntem % 75 doğruluk elde etti ve bireysel derin öğrenme mimarilerine kıyasla kesinlik ve duyarlılık metriklerinde önemli artışlar sağladı. Önerilen model geliştirilebilecek bir mobil uygulama sayesinde, büyük ölçekli taramalarda tıp profesyonelleri için yardımcı bir karar destek sistemi olarak kullanılabilecektir. Sonuçlara bakıldığında en çok kullandığımız uzuvlarımızdan biri olan eldeki tırnaklarımızda meydana gelen hastalıkların (uzaktan) erken tespit edilmesinin hastane ziyaretlerini ve maliyetleri azaltabileceğini öngörüyoruz. Ayrıca önerilen yöntem cilt hastalıkları ve ben analizi için kullanılan dermatoskopi cihazlarına entegre edilebilir.

Anahtar Kelimeler

DETECTION OF NAIL DISEASES USING ENSEMBLE MODEL BASED ON MAJORITY VOTING

Abstract

Nail diseases are disorders that can have serious effects on human quality of life. With the developing computational methods and technology, anomalies on the nail may be detected quickly and in a non-invasive way. This study proposes a model that provides better performance by combining the results of different deep learning networks with the ensemble learning method. The performance of 7 different deep learning architectures was examined using a database containing 17 disease classes. The proposed method achieved 75 % accuracy, resulting in significant increases in precision and recall metrics compared to individual deep-learning architectures. Thanks to a mobile application that will be developed, the proposed model for large-scale screening may be used as an assistive decision support system for medical professionals. When the results are observed, we predict that early detection of nail diseases (in a remote way) on the hand, which is one of our most used limbs, can reduce hospital visits and costs. In addition, the proposed method can be integrated into dermatoscopy devices used for skin diseases and mole analysis.

Keywords

References

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Details

Primary Language

English

Subjects

Electrical Engineering

Journal Section

Research Article

Authors

Senar Ali Yamaç
0000-0003-0880-9202
Türkiye

Orhun Kuyucuoğlu
0000-0002-3415-6068
Türkiye

Şeyma Begüm Köseoğlu
0000-0001-7621-6850
Türkiye

Sezer Ulukaya ^*
0000-0003-0473-7547
Türkiye

Publication Date

March 15, 2023

Submission Date

December 26, 2022

Acceptance Date

February 4, 2023

Published in Issue

Year 2023 Volume: 26 Number: 1

DOI

https://doi.org/10.17780/ksujes.1224006

IZ

https://izlik.org/JA85RB33KL

Cite

RIS / Bibtex

APA

Yamaç, S. A., Kuyucuoğlu, O., Köseoğlu, Ş. B., & Ulukaya, S. (2023). DETECTION OF NAIL DISEASES USING ENSEMBLE MODEL BASED ON MAJORITY VOTING. Kahramanmaraş Sütçü İmam Üniversitesi Mühendislik Bilimleri Dergisi, 26(1), 250-260. https://doi.org/10.17780/ksujes.1224006