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Orthodontic Implementation of Machine Learning Algorithms for Predicting Some Linear Dental Arch Measurements and
Aras Maruf Rauf1, Trefa Mohammed Ali Mahmood1, Miran Hikmat Mohammed2
1Department of Pedodontics, Orthodontics and Preventive Dentistry, College of Dentistry, University of Sulaimani, Sulaimaniyah 46001, Iraq.
Medicina (Kaunas, Lithuania)
|November 25, 2023
Summary
Artificial intelligence accurately predicts dental arch width using machine learning, aiding orthodontic diagnosis and preventing future crowding in patients. This technology enhances treatment planning for both growing and adult individuals.
Area of Science:
- Orthodontics
- Artificial Intelligence
- Machine Learning
Background:
- Technological advancements are revolutionizing orthodontic diagnosis and treatment planning.
- Predicting dental arch width is crucial for preventing malocclusion.
Purpose of the Study:
- To implement AI for predicting arch width in growing and adult orthodontic patients.
- To utilize machine learning as a diagnostic tool for early intervention.
Main Methods:
- Utilized 450 intraoral scan (IOS) images from orthodontic patients.
- Measured inter-canine, inter-premolar, and inter-molar widths digitally.
- Applied k-nearest neighbor (KNN) and linear regression (LR) machine learning models using Python.
Main Results:
- K-nearest neighbor (KNN) demonstrated superior prediction accuracy compared to linear regression (LR).
- The machine learning models achieved approximately 99% prediction accuracy.
- Successfully predicted linear dental arch measurements.
Conclusions:
- Machine learning can significantly enhance orthodontic diagnosis and treatment planning.
- AI-driven prediction of arch width can prevent anterior segment malocclusion.
- This approach offers a valuable tool for preventive orthodontics.
