Evolution And Implementation Of Artificial Intelligence In Orthodontics – A Literature Review
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Keywords

Artificial Intelligence (AI)
Orthodontics
Machine Learning (ML)
Deep Learning (DL)
Personalized Treatment Planning
Radiographic Interpretation

Abstract

AI in orthodontics has transformed the diagnostic and treatment approaches making them more accurate, effective and productive regarding the patient’s health. In this concerning review, the features of applying AI in orthodontics are discussed, with a focus on such sections as automated cephalometric analysis, radiographic interpretation, predictions of tooth movement, and individual treatment planning. Using ML, DL and neural networks in orthodontia, the roles of the orthodontist have been made easier through optimizing the FACIAL landmark detection, TOOTH segmentation, and CBCT analysis. In addition, AI makes a significant contribution to more rational decision-making as concerns particular stages of treatment – including extractions and surgical orthodontic procedures such as orthognathic surgeries. This in turn ultimately leads to shorter treatment duration, lesser discomfort and better cosmetic results due to the development of better care plans. However, access to AI in orthodontic practice is restrained today by factors like data privacy and protection issues, algorithmic and deployed bias, or implementation costs, among others. This is important for alleviating the challenges hindering unequal distribution of artificial intelligence driven care and to realize the optimum benefits across the extensive related domain. With the development of AI in the process, the application of AI in orthodontic practice and improved patient care should increase in the future, which could lead to evermore innovative treatments.

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