CANLI
Yükleniyor Veriler getiriliyor…
/ Makaleler / Scopus Detay
Scopus YÖKSİS Eşleşti

A deep learning based decision support system for diagnosis of Temporomandibular joint disorder

Applied Acoustics · Kasım 2021

YÖKSİS DOI Eşleşmesi Bulundu

Bu Scopus makalesi YÖKSİS veritabanında da kayıtlı. Aşağıda YÖKSİS verilerini görebilirsiniz.

YÖKSİS Kayıtları
A deep learning based decision support system for diagnosis of Temporomandibular joint disorder
Applied Acoustics · 2021 SCI-Expanded
DOKTOR ÖĞRETİM ÜYESİ UĞUR TAŞKIRAN →
A deep learning based decision support system for diagnosis of Temporomandibular joint disorder
Applied Acoustics · 2021 SCI-Expanded
PROFESÖR MEHMET ÇUNKAŞ →

Makale Bilgileri

DergiApplied Acoustics
Yayın TarihiKasım 2021
Cilt / Sayfa182
DOI10.1016/j.apacoust.2021.108292
Scopus ID2-s2.0-85109905258
Özet Temporomandibular Joint sounds are a very common disorder in the general population. Temporomandibular Disorder (TMD) is any discomfort related to Temporomandibular Joint (TMJ). In this paper, a novel decision support system based on deep learning and neural network algorithms for diagnosis of Temporomandibular Joint disorder is introduced. A non-invasive device is designed for the recording of TMJ sounds. An interface is developed that will facilitate the dentist to operate on the recorded audio data. The collected data consist of the patient's left and right Temporomandibular Joint sound, ambient noise sound, the patient's clinical data, the dentist's notes about the patient, diagnosis, and treatment. Then signal processing, artificial neural network and deep learning algorithms are used to classify these measurements, and thus, the method that decides about the patient's condition is developed. Frequency, statistical and deep learning-based methods are compared in terms of classification success. The results show that the classification success of the classification method based on deep learning is consistently over 94.5% and it is more successful than the previous two methods. The proposed system can give the physician an idea about the effectiveness of the treatment methods applied to the patient in order to treat joint sounds which are among the important symptoms of TMD.

Yazarlar (2)

1
Uğur Taşkıran
2
Mehmet Çunkaş

Anahtar Kelimeler

Artificial neural networks Deep learning Digital signal processing Temporomandibular joint disorder Temporomandibular Joint sound

Kurumlar

Selçuk Üniversitesi
Selçuklu Turkey

Metrikler

7
Atıf
2
Yazar
5
Anahtar Kelime

Sistemimizdeki Yazarlar

UT
UĞUR TAŞKIRAN
DOKTOR ÖĞRETİM ÜYESİ

Hızlı Erişim

DOI ile aç Scopus'ta aç Makaleler listesi