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

Applied Acoustics · Kasım 2021

YÖKSİS Kayıtları

Applied Acoustics · 2021 SCI-Expanded

Dr. Öğr. Üyesi UĞUR TAŞKIRAN →

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

Applied Acoustics · 2021 SCI-Expanded

Prof. Dr. MEHMET ÇUNKAŞ →

YÖKSİS Kayıtları — ISSN Eşleşmesi

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

2021 ISSN: 0003-682X SCI-Expanded Q2

Dr. Öğr. Üyesi UĞUR TAŞKIRAN →

10.1016/j.apacoust.2021.108292

Makale Bilgileri

Dergi Applied Acoustics

ISSN0003682X

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.