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BMC Oral Health

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Open Access 01-12-2023 | Artificial Intelligence | Research

Application of entire dental panorama image data in artificial intelligence model for age estimation

Authors: Se Hoon Kahm, Ji-Youn Kim, Seok Yoo, Soo-Mi Bae, Ji-Eun Kang, Sang Hwa Lee

Published in: BMC Oral Health | Issue 1/2023

Abstract

Background

Accurate age estimation is vital for clinical and forensic purposes. With the rapid advancement of artificial intelligence(AI) technologies, traditional methods relying on tooth development, while reliable, can be enhanced by leveraging deep learning, particularly neural networks. This study evaluated the efficiency of an AI model by applying the entire panoramic image for age estimation. The outcome performances were analyzed through supervised learning (SL) models.

Methods

Total of 27,877 dental panorama images from 5 to 90 years of age were classified by 2 types of grouping. In type 1 they were classified by each age and in type 2, applying heuristic grouping, the age over 20 years were classified by every 5 years. Wide ResNet (WRN) and DenseNet (DN) were used for supervised learning. In addition, the analysis with ± 3 years of deviation in both types were performed.

Results

For the DN model, while the type 1 grouping achieved an accuracy of 0.1016 and F1 score of 0.058, the type 2 achieved an accuracy of 0.3146 and F1 score of 0.2027. Incorporating ± 3years of deviation, the accuracy of type 1 and 2 were 0.281, 0.7323 respectively; and the F1 score were 0.1768, 0.6583 respectively. For the WRN model, while the type 1 grouping achieved an accuracy of 0.1041 and F1 score of 0.0599, the type 2 achieved an accuracy of 0.3182 and F1 score of 0.2071. Incorporating ± 3years of deviation, the accuracy of type 1 and 2 were 0.2716, 0.7323 respectively; and the F1 score were 0.1709, 0.6437 respectively.

Conclusions

The application of entire panorama image data for supervised with classification by heuristics grouping with ± 3years of deviation for supervised learning models and demonstrated satisfactory outcome for the age estimation.

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Title: Application of entire dental panorama image data in artificial intelligence model for age estimation
Authors: Se Hoon Kahm
Ji-Youn Kim
Seok Yoo
Soo-Mi Bae
Ji-Eun Kang
Sang Hwa Lee
Publication date: 01-12-2023
Publisher: BioMed Central
Keyword: Artificial Intelligence
Published in: BMC Oral Health / Issue 1/2023
Electronic ISSN: 1472-6831
DOI: https://doi.org/10.1186/s12903-023-03745-x

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Springer Medicine

Application of entire dental panorama image data in artificial intelligence model for age estimation

Abstract

Background

Methods

Results

Conclusions

Keynote webinar | Spotlight on medication adherence

Springer Medicine

Abstract

Background

Methods

Results

Conclusions

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