ENHANCING THE DIAGNOSIS AND MANAGEMENT OF TEMPOROMANDIBULAR JOINT PAIN DYSFUNCTION SYNDROME USING ARTIFICIAL INTELLIGENCE TECHNOLOGIES

Pain dysfunction syndrome of the temporomandibular joint (TMJ) is common in dental practice and is characterized by the complexity of its diagnosis and treatment. This thesis analyzes the potential of artificial intelligence (AI) technologies to improve the effectiveness of diagnosing and managing TMJ pain dysfunction syndrome. AI-based algorithms enable comprehensive assessment of clinical, radiological, and functional parameters, allowing early detection, individualized prognosis, and development of personalized treatment plans. The study results demonstrate that AI technologies provide higher accuracy and faster performance compared to conventional diagnostic methods.