Intelligence-Assisted Diagnosis and Treatment Planning in Orthodontics: A Systematic Review

Introduction: The use of artificial intelligence (AI) in orthodontics has rapidly developed in recent years. This systematic review aims to evaluate the effectiveness and accuracy of AI applications in orthodontic diagnosis and treatment planning. Methods: Data collection in this literature review followed the Preferred Reporting Items for Systematic Review and Meta-Analysis (PRISMA) guidelines. Articles published in the last 5 years were screened from various literature sources through PubMed and Science Direct databases. Results: Out of 672 identified articles, 15 studies met the inclusion criteria. The most common AI applications included cephalometric analysis, prediction of extraction needs, and treatment outcome simulations. The majority of studies reported AI accuracy comparable to or better than conventional methods. Several studies demonstrated significant reduction in diagnosis time with the use of AI. Conclusion: Available evidence indicates great potential for AI in improving the accuracy and efficiency of orthodontic diagnosis and treatment planning. However, further research with more rigorous designs and larger sample sizes is needed to validate the effectiveness of AI in daily clinical practice.