[Research and prospects of deep learning in the field of temporomandibular disorders].

Temporomandibular disorders (TMD) is one of the most clinically common oral diseases.It covers a range of conditions involving the temporomandibular joint (TMJ) and its adjacent muscles and tissues. Patients typically experience discomfort symptoms such as joint clicking, TMJ pain, chewing muscle discomfort, and jaw movement dysfunction. Given the complexity of the etiology of TMD, the diversity and non-specificity of symptoms, how to accurately diagnose and formulate the best treatment plan has become a challenging issue that urgently needs to be addressed in clinical practice. In recent years, the rapid development of artificial intelligence technology, especially deep learning (DL) technology, has brought a revolutionary driving force to medical diagnosis and treatment. This article aims to review the current application of DL in the diagnosis and treatment of TMD, discuss the challenges faced, and provide prospects for future development, in order to have a deeper understanding and reflection on the application of DL in the diagnosis and treatment of TMD.

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Publication Details

Journal
PubMed
Published
2025-10-09
DOI
https://doi.org/10.3760/cma.j.cn112144-20250507-00171
Primary Topic
Medical and Biological Sciences
Type
article
Field-Weighted Citation Impact
0.00
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article

[Research and prospects of deep learning in the field of temporomandibular disorders].

Yuanming Yang, Jun Wang, Lin Yin
PubMed
Medical and Biological Sciences
article

[Research and prospects of deep learning in the field of temporomandibular disorders].

Yuanming Yang, Jun Wang, Lin Yin
article en

Abstract

Temporomandibular disorders (TMD) is one of the most clinically common oral diseases.It covers a range of conditions involving the temporomandibular joint (TMJ) and its adjacent muscles and tissues. Patients typically experience discomfort symptoms such as joint clicking, TMJ pain, chewing muscle discomfort, and jaw movement dysfunction. Given the complexity of the etiology of TMD, the diversity and non-specificity of symptoms, how to accurately diagnose and formulate the best treatment plan has become a challenging issue that urgently needs to be addressed in clinical practice. In recent years, the rapid development of artificial intelligence technology, especially deep learning (DL) technology, has brought a revolutionary driving force to medical diagnosis and treatment. This article aims to review the current application of DL in the diagnosis and treatment of TMD, discuss the challenges faced, and provide prospects for future development, in order to have a deeper understanding and reflection on the application of DL in the diagnosis and treatment of TMD.

PubMedVol. 60(10)
Nanchang University (CN), Second Affiliated Hospital of Nanchang University (CN)
Openalex Percentile: Top 46%
Medical and Biological Sciences
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