Machine Learning for Evaluating and Diagnosing Temporomandibular Disorders
Trial statusNot yet recruiting
Trial phaseNot applicable
Trial typeInterventional
Biological sexAll
Age18-70
SponsorEn Chu Kong Hospital
About this trial
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.
Eligibility criteria
Qualifiers
Patients diagnosed with temporomandibular disorders (TMDs) screened by the Department of Dentistry, Division of Oral and Maxillofacial Surgery at En Chu Kong Hospital, who have failed to respond to analgesic treatment for at least one week.
Patients clinically examined and identified as having pain predominantly originating from muscles associated with mandibular movement.
Patients aged between 18 and 70 years (inclusive) with full legal capacity.
Patients who are willing to participate in the study and provide written informed consent.
Disqualifiers
Patients meeting any of the following clinical scale thresholds: Generalized Anxiety Disorder-7 (GAD-7)≥ 10, Patient Health Questionnaire-9 (PHQ-9) ≥ 15, Patient Health Questionnaire-15 (PHQ-15) ≥ 10, or Pittsburgh Sleep Quality Index (PSQI) > 5.
Patients with tumors of the temporomandibular joint (TMJ) or head and neck region.
Patients with acute or chronic infections.
Patients with a history of neuropathy or stroke.
Trial design
Treatments tested in this trial
- Low-Level Laser Acupuncture
- Proprioceptive Training
- Stabilization Splint Treatment
Treatment groups
180 Participants
are divided into 3 treatment groupsLocations
Sponsors and collaborators
En Chu Kong Hospital
Lead sponsor
National Yang Ming Chiao Tung University
Collaborator
Source ClinicalTrials.gov