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Cited by in F6Publishing

For:	Estai M, Tennant M, Gebauer D, Brostek A, Vignarajan J, Mehdizadeh M, Saha S. Evaluation of a deep learning system for automatic detection of proximal surface dental caries on bitewing radiographs. Oral Surgery, Oral Medicine, Oral Pathology and Oral Radiology 2022. [DOI: 10.1016/j.oooo.2022.03.008] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 1.0] [Reference Citation Analysis]

For:

Estai M, Tennant M, Gebauer D, Brostek A, Vignarajan J, Mehdizadeh M, Saha S. Evaluation of a deep learning system for automatic detection of proximal surface dental caries on bitewing radiographs. Oral Surgery, Oral Medicine, Oral Pathology and Oral Radiology 2022. [DOI: 10.1016/j.oooo.2022.03.008] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 1.0] [Reference Citation Analysis]

Number	Citing Articles
1	Baseri Saadi S, Moreno-rabié C, van den Wyngaert T, Jacobs R. Convolutional neural network for automated classification of osteonecrosis and related mandibular trabecular patterns. Bone Reports 2022;17:101632. [DOI: 10.1016/j.bonr.2022.101632] [Reference Citation Analysis]
2	Fariza A, Asmara R, Rojaby MOF, Astuti ER, Putra RH. Evaluation of Convolutional Neural Network for Automatic Caries Detection in Digital Radiograph Panoramic on Small Dataset. 2022 International Conference on Data and Software Engineering (ICoDSE) 2022. [DOI: 10.1109/icodse56892.2022.9972183] [Reference Citation Analysis]
3	Thanh MTG, Van Toan N, Ngoc VTN, Tra NT, Giap CN, Nguyen DM. Deep Learning Application in Dental Caries Detection Using Intraoral Photos Taken by Smartphones. Applied Sciences 2022;12:5504. [DOI: 10.3390/app12115504] [Cited by in Crossref: 1] [Article Influence: 1.0] [Reference Citation Analysis]