AIMC Topic: Temporomandibular Joint Disorders

Clear Filters Showing 51 to 55 of 55 articles

Understanding Occlusion and Temporomandibular Joint Function Using Deep Learning and Predictive Modeling.

Clinical and experimental dental research
OBJECTIVES: Advancements in artificial intelligence (AI)-driven predictive modeling in dentistry are outpacing the clinical translation of research findings. Predictive modeling uses statistical methods to anticipate norms related to TMJ dynamics, co...

An Explainable and Conformal AI Model to Detect Temporomandibular Joint Involvement in Children Suffering from Juvenile Idiopathic Arthritis.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Juvenile idiopathic arthritis (JIA) is the most common rheumatic disease during childhood and adolescence. The temporomandibular joints (TMJ) are among the most frequently affected joints in patients with JIA, and mandibular growth is especially vuln...

Temporomandibular Joint Disorders Multi-Class Classification Using Deep Learning.

Studies in health technology and informatics
Temporomandibular joint (TMJ) disorders have been misinterpreted by various normal TMJ features leading to treatment failure. This study assessed deep learning algorithms, DenseNet-121 and InceptionV3, for multi-class classification of TMJ normal var...

[Design and performance analysis of elastic temporomandibular joint structure of biomimetic masticatory robot].

Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi
Masticatory robots have a broad application prospect in the field of denture material tests and mandible rehabilitation. Mechanism type of temporomandibular joint structure is an important factor influencing the performance of the masticatory robot. ...