AIMC Topic: Temporomandibular Joint Disorders

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Relation of vitamin D and BsmI variant with temporomandibular diseases in the Turkish population.

The British journal of oral & maxillofacial surgery
Vitamin D (VD) levels and several variants in the vitamin D receptor (VDR) gene are associated with the occurrence of diseases of the bones and cartilage. The aim of this research was to study and compare the association of the BsmI variant in the VD...

Osteoarthritis of the Temporomandibular Joint can be diagnosed earlier using biomarkers and machine learning.

Scientific reports
After chronic low back pain, Temporomandibular Joint (TMJ) disorders are the second most common musculoskeletal condition affecting 5 to 12% of the population, with an annual health cost estimated at $4 billion. Chronic disability in TMJ osteoarthrit...

Automatic mandibular canal detection using a deep convolutional neural network.

Scientific reports
The practicability of deep learning techniques has been demonstrated by their successful implementation in varied fields, including diagnostic imaging for clinicians. In accordance with the increasing demands in the healthcare industry, techniques fo...

Minimally Invasive Approach for Diagnosing TMJ Osteoarthritis.

Journal of dental research
This study's objectives were to test correlations among groups of biomarkers that are associated with condylar morphology and to apply artificial intelligence to test shape analysis features in a neural network (NN) to stage condylar morphology in te...

Evaluation of Effect of Glucosamine-Chondroitin Sulfate, Tramadol, and Sodium Hyaluronic Acid on Expression of Cytokine Levels in Internal Derangement of Temporomandibular Joint.

The journal of contemporary dental practice
AIM: Evaluation of the effect of glucosamine-chondroitin combination, tramadol, and sodium hyaluronic acid in temporomandibular joint (TMJ) disorders and its impact on the expression of various cytokines such as IL-6, IL-1β, TNF-α, and PGE2.

A web-based system for neural network based classification in temporomandibular joint osteoarthritis.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
OBJECTIVE: The purpose of this study is to describe the methodological innovations of a web-based system for storage, integration and computation of biomedical data, using a training imaging dataset to remotely compute a deep neural network classifie...

Perspectives on next steps in classification of oro-facial pain - part 1: role of ontology.

Journal of oral rehabilitation
The purpose of this study was to review existing principles of oro-facial pain classifications and to specify design recommendations for a new system that would reflect recent insights in biomedical classification systems, terminologies and ontologie...

Magnetic resonance image generation using enhanced TransUNet in temporomandibular disorder patients.

Dento maxillo facial radiology
OBJECTIVES: Temporomandibular disorder (TMD) patients experience a variety of clinical symptoms, and MRI is the most effective tool for diagnosing temporomandibular joint (TMJ) disc displacement. This study aimed to develop a transformer-based deep l...

Deep learning image enhancement for confident diagnosis of TMJ osteoarthritis in zero-TE MR imaging.

Dento maxillo facial radiology
OBJECTIVES: This study aimed to evaluate the effectiveness of deep learning method for denoising and artefact reduction (AR) in zero echo time MRI (ZTE-MRI). Also, clinical applicability was evaluated by comparing image diagnosis to the temporomandib...