Abstract
The temporomandibular joints (TMJs) consist of complex formation of bones, muscles and tendons. Pain in jaw area is a result of disorders and injury of these structures. This TMJ disorder causes tinnitus headaches, vertigo, migraines and several TMJ arthritides. Prediction of TMJ syndrome is complex because this joint is different from the load joint of knee or hip. For diagnosis and prediction of TMJ syndrome, artificial intelligent techniques are indeed worth exploring. In this paper, the proposed model is based on neural network theory which will be helpful to sense whether a patient is suffering from TMJ disorder or not. This model automatically predicts the TMJ on the basis of risk factors and symptoms given by the patients.
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Sharma, N., Dar, I.G., Kumar, J., Khan, A., Thakur, A. (2019). Temporomandibular Joint Syndrome Prediction Using Neural Network. In: Ray, K., Sharan, S., Rawat, S., Jain, S., Srivastava, S., Bandyopadhyay, A. (eds) Engineering Vibration, Communication and Information Processing. Lecture Notes in Electrical Engineering, vol 478. Springer, Singapore. https://doi.org/10.1007/978-981-13-1642-5_1
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DOI: https://doi.org/10.1007/978-981-13-1642-5_1
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