What does this research mean for the field?

Clinical factors including bruxism and sleep disturbance, along with MRI-identified structural damage, are significant predictors of chronic temporomandibular disorders that can be accurately modeled using machine learning. Novelty: ClaimNovelty.INCREMENTAL. Consensus alignment: ConsensusAlignment.NEUTRAL.

September 29, 2025Communications MedicineOpen Access

Clinical and MRI markers for acute vs chronic temporomandibular disorders using a machine learning and deep neural networks

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Authors

YLYeon‐Hee LeeSeoul National University Dental Hospital SJSeonggwang JeonHanyang University DKDohoon KimKorea Advanced Institute of Science and Technology

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Cite This Study

Lee et al. (2025) studied this question.

synapsesocial.com/papers/6a2956e7d3590f1fbd9ff2a6 https://doi.org/10.1038/s43856-025-01081-5

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September 29, 2025Communications MedicineOpen Access

Clinical and MRI markers for acute vs chronic temporomandibular disorders using a machine learning and deep neural networks

View Full Paper

Ask AI

Bookmark

Authors

YLYeon‐Hee LeeSeoul National University Dental Hospital SJSeonggwang JeonHanyang University DKDohoon KimKorea Advanced Institute of Science and Technology

Discussion

Member takes

Implication

Key Points

Key points are not available for this paper at this time.

Cite This Study

Lee et al. (2025) studied this question.

synapsesocial.com/papers/6a2956e7d3590f1fbd9ff2a6 https://doi.org/10.1038/s43856-025-01081-5

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