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Automated deep learning for classification of dental implant radiographs using a large multi-center dataset

Authors
 Wonse Park  ;  Jong-Ki Huh  ;  Jae-Hong Lee 
Citation
 SCIENTIFIC REPORTS, Vol.13(1) : 4862, 2023-03 
Journal Title
SCIENTIFIC REPORTS
Issue Date
2023-03
MeSH
Algorithms ; Deep Learning* ; Dental Implants* ; Humans ; Radiography ; Radiography, Panoramic / methods
Abstract
This study aimed to evaluate the accuracy of automated deep learning (DL) algorithm for identifying and classifying various types of dental implant systems (DIS) using a large-scale multicenter dataset. Dental implant radiographs of pos-implant surgery were collected from five college dental hospitals and 10 private dental clinics, and validated by the National Information Society Agency and the Korean Academy of Oral and Maxillofacial Implantology. The dataset contained a total of 156,965 panoramic and periapical radiographic images and comprised 10 manufacturers and 27 different types of DIS. The accuracy, precision, recall, F1 score, and confusion matrix were calculated to evaluate the classification performance of the automated DL algorithm. The performance metrics of the automated DL based on accuracy, precision, recall, and F1 score for 116,756 panoramic and 40,209 periapical radiographic images were 88.53%, 85.70%, 82.30%, and 84.00%, respectively. Using only panoramic images, the DL algorithm achieved 87.89% accuracy, 85.20% precision, 81.10% recall, and 83.10% F1 score, whereas the corresponding values using only periapical images achieved 86.87% accuracy, 84.40% precision, 81.70% recall, and 83.00% F1 score, respectively. Within the study limitations, automated DL shows a reliable classification accuracy based on large-scale and comprehensive datasets. Moreover, we observed no statistically significant difference in accuracy performance between the panoramic and periapical images. The clinical feasibility of the automated DL algorithm requires further confirmation using additional clinical datasets. © 2023, The Author(s).
Files in This Item:
T202302414.pdf Download
DOI
10.1038/s41598-023-32118-1
Appears in Collections:
2. College of Dentistry (치과대학) > Dept. of Advanced General Dentistry (통합치의학과) > 1. Journal Papers
2. College of Dentistry (치과대학) > Dept. of Oral and Maxillofacial Surgery (구강악안면외과학교실) > 1. Journal Papers
Yonsei Authors
Park, Wonse(박원서) ORCID logo https://orcid.org/0000-0002-2081-1156
Huh, Jong Ki(허종기) ORCID logo https://orcid.org/0000-0002-7381-3972
URI
https://ir.ymlib.yonsei.ac.kr/handle/22282913/194140
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