Machine Learning for Evaluating and Diagnosing Temporomandibular Disorders
Sponsor: En Chu Kong Hospital • ClinicalTrials.gov ID: NCT07771296
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This study aims to improve clinical efficiency and effectiveness in treating Temporomandibular Disorders (TMD). The researchers will integrate machine learning technology with clinical examination data, CBCT, and MRI to identify the core underlying issues of each patient. Based on this precise, AI-assisted diagnosis, the study will implement a tailored treatment framework. The final goal is to develop predictive algorithms that can determine MRI necessity while ensuring that clinical interventions are highly targeted, efficient, and successful.
Interventions
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Low-Level Laser Acupuncture
(Device)
Laser acupuncture targets the Xiaguan (ST7), Yifeng (SJ17), and bilateral Fengchi (GB20) points once weekly. For the LLLT+LLLT group, active laser is given for 4 weeks. For the Sham+LLLT group, sham laser is given for the first 2 weeks followed by 2 weeks of active laser.
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Proprioceptive Training
(Behavioral)
Includes gentle teeth tapping, tongue-to-palate contact, and neutral head-neck posture exercises, performed three times daily for 4 weeks.
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Stabilization Splint Treatment
(Device)
Standard conservative clinical care utilizing a hard acrylic flat-plane stabilization splint (centric stabilization splint) for TMD management. The splint is customized to provide even, bilateral occlusal contact in the musculoskeletal stable position during the 4-week trial period.
Eligibility criteria
Conditions
Locations
- En Chu Kong Hospital — New Taipei City, Sanxia, Taiwan
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Data sourced from ClinicalTrials.gov, a service of the U.S. National Institutes of Health.
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