Korean J Orthod.  2022 Mar;52(2):102-111. 10.4041/kjod.2022.52.2.102.

Use of automated artificial intelligence to predict the need for orthodontic extractions

• Del Real A
• Del Real O
• Sardina S
• Oyonarte R

• KMID: 2527454
• DOI: http://doi.org/10.4041/kjod.2022.52.2.102

Abstract

Objective
To develop and explore the usefulness of an artificial intelligence system for the prediction of the need for dental extractions during orthodontic treatments based on gender, model variables, and cephalometric records.
Methods
The gender, model variables, and radiographic records of 214 patients were obtained from an anonymized data bank containing 314 cases treated by two experienced orthodontists. The data were processed using an automated machine learning software (Auto-WEKA) and used to predict the need for extractions.
Results
By generating and comparing several prediction models, an accuracy of 93.9% was achieved for determining whether extraction is required or not based on the model and radiographic data. When only model variables were used, an accuracy of 87.4% was attained, whereas a 72.7% accuracy was achieved if only cephalometric information was used.
Conclusions
The use of an automated machine learning system allows the generation of orthodontic extraction prediction models. The accuracy of the optimal extraction prediction models increases with the combination of model and cephalometric data for the analytical process.

Keyword

Extraction vs. non-extraction; Computer algorithm; Decision tree; Orthodontic Index

Reference

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