AIMC Topic: Temporomandibular Joint Disorders

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Distinguishing acute and chronic TMD in adolescent patients.

Scientific reports
This retrospective cross-sectional study aimed to elucidate the clinical and imaging characteristics of chronic temporomandibular disorder (TMD) compared to acute TMD in adolescents, and to identify factors associated with symptom chronicity. The stu...

Semi-automatic detection of anteriorly displaced temporomandibular joint discs in magnetic resonance images using machine learning.

BMC oral health
BACKGROUND: Accurate diagnosis of anterior disc displacement (ADD) is essential for managing temporomandibular joint disorders (TMJ). This study employed machine learning (ML) to automatically detect anteriorly displaced TMJ discs in magnetic resonan...

Comparative study of technical and patient-related question answering quality of DeepSeek-R1 and ChatGPT-4o in the field of oral and maxillofacial surgery.

Oral and maxillofacial surgery
BACKGROUND: Artificial Intelligence (AI) technologies demonstrate potential as supplementary tools in healthcare, particularly in surgery, where they assist with preoperative planning, intraoperative decisions, and postoperative monitoring. In oral a...

Deep Learning for Ultrasonographic Assessment of Temporomandibular Joint Morphology.

Tomography (Ann Arbor, Mich.)
BACKGROUND: Temporomandibular joint (TMJ) disorders are a significant cause of orofacial pain. Artificial intelligence (AI) has been successfully applied to other imaging modalities but remains underexplored in ultrasonographic evaluations of TMJ.

Automated pediatric TMJ articular disk identification and displacement classification in MRI with machine learning.

Journal of dentistry
OBJECTIVE: To evaluate the performance of an automated two-step model interpreting pediatric temporomandibular joint (TMJ) magnetic resonance imaging (MRI) using artificial intelligence (AI). Using deep learning techniques, the model first automatica...

Automated diagnosis and classification of temporomandibular joint degenerative disease via artificial intelligence using CBCT imaging.

Journal of dentistry
OBJECTIVES: In this study, artificial intelligence (AI) techniques were used to achieve automated diagnosis and classification of temporomandibular joint (TMJ) degenerative joint disease (DJD) on cone beam computed tomography (CBCT) images.

Artificial intelligence-enhanced diagnosis of degenerative joint disease using temporomandibular joint panoramic radiography and joint noise data.

Scientific reports
This study aimed to develop an artificial intelligence (AI) model for the screening of degenerative joint disease (DJD) using temporomandibular joint (TMJ) panoramic radiography and joint noise data. A total of 2631 TMJ panoramic images were collecte...

Detecting the articular disk in magnetic resonance images of the temporomandibular joint using YOLO series.

Dental materials journal
The purpose of this study was to construct an artificial intelligence object detection model to detect the articular disk from temporomandibular joint (TMJ) magnetic resonance (MR) images using YOLO series. The study included two experiments using da...

Role of artificial intelligence in magnetic resonance imaging-based detection of temporomandibular joint disorder: a systematic review.

The British journal of oral & maxillofacial surgery
This systematic review aimed to evaluate the application of artificial intelligence (AI) in the identification of temporomandibular joint (TMJ) disc position in normal or temporomandibular joint disorder (TMD) individuals using magnetic resonance ima...