An overview of deep learning in the field of dentistry
- Author:
Jae Joon HWANG
1
;
Yun Hoa JUNG
;
Bong Hae CHO
;
Min Suk HEO
Author Information
- Publication Type:Review
- Keywords: Artificial Intelligence; Deep Learning; Dentistry; Radiology
- MeSH: Artificial Intelligence; Dataset; Dentistry; Learning
- From:Imaging Science in Dentistry 2019;49(1):1-7
- CountryRepublic of Korea
- Language:English
- Abstract: PURPOSE: Artificial intelligence (AI), represented by deep learning, can be used for real-life problems and is applied across all sectors of society including medical and dental field. The purpose of this study is to review articles about deep learning that were applied to the field of oral and maxillofacial radiology. MATERIALS AND METHODS: A systematic review was performed using Pubmed, Scopus, and IEEE explore databases to identify articles using deep learning in English literature. The variables from 25 articles included network architecture, number of training data, evaluation result, pros and cons, study object and imaging modality. RESULTS: Convolutional Neural network (CNN) was used as a main network component. The number of published paper and training datasets tended to increase, dealing with various field of dentistry. CONCLUSION: Dental public datasets need to be constructed and data standardization is necessary for clinical application of deep learning in dental field.
