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For: Bayrakdar IS, Orhan K, Akarsu S, Çelik Ö, Atasoy S, Pekince A, Yasa Y, Bilgir E, Sağlam H, Aslan AF, Odabaş A. Deep-learning approach for caries detection and segmentation on dental bitewing radiographs. Oral Radiol 2021. [PMID: 34807344 DOI: 10.1007/s11282-021-00577-9] [Cited by in Crossref: 5] [Cited by in F6Publishing: 7] [Article Influence: 2.5] [Reference Citation Analysis]
Number Citing Articles
1 Kurt-bayrakdar S, Uğurlu M, Yavuz MB, Sali N, Bayrakdar İŞ, Çelik Ö, Köse O, Beklen A, Saylan BCU, Jagtap R, Orhan K. Detection of Tooth Numbering, Frenulum, Gingival Hyperplasia and Gingival Inflammation on Dental Photographs Using Convolutional Neural Network Algorithms: An Initial Study.. [DOI: 10.21203/rs.3.rs-2222628/v1] [Reference Citation Analysis]
2 Sukegawa S, Tanaka F, Hara T, Yoshii K, Yamashita K, Nakano K, Takabatake K, Kawai H, Nagatsuka H, Furuki Y. Deep learning model for analyzing the relationship between mandibular third molar and inferior alveolar nerve in panoramic radiography. Sci Rep 2022;12:16925. [PMID: 36209283 DOI: 10.1038/s41598-022-21408-9] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 1.0] [Reference Citation Analysis]
3 Barayan MA, Qawas AA, Alghamdi AS, Alkhallagi TS, Al-dabbagh RA, Aldabbagh GA, Linjawi AI. Effectiveness of Machine Learning in Assessing the Diagnostic Quality of Bitewing Radiographs. Applied Sciences 2022;12:9588. [DOI: 10.3390/app12199588] [Reference Citation Analysis]
4 Ramana Kumari A, Nagaraja Rao S, Ramana Reddy P. Design of hybrid dental caries segmentation and caries detection with meta-heuristic-based ResneXt-RNN. Biomedical Signal Processing and Control 2022;78:103961. [DOI: 10.1016/j.bspc.2022.103961] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 1.0] [Reference Citation Analysis]
5 Thurzo A, Urbanová W, Novák B, Czako L, Siebert T, Stano P, Mareková S, Fountoulaki G, Kosnáčová H, Varga I. Where Is the Artificial Intelligence Applied in Dentistry? Systematic Review and Literature Analysis. Healthcare (Basel) 2022;10:1269. [PMID: 35885796 DOI: 10.3390/healthcare10071269] [Cited by in Crossref: 5] [Cited by in F6Publishing: 5] [Article Influence: 5.0] [Reference Citation Analysis]
6 Khanagar SB, Alfouzan K, Awawdeh M, Alkadi L, Albalawi F, Alfadley A. Application and Performance of Artificial Intelligence Technology in Detection, Diagnosis and Prediction of Dental Caries (DC)—A Systematic Review. Diagnostics 2022;12:1083. [DOI: 10.3390/diagnostics12051083] [Cited by in Crossref: 2] [Cited by in F6Publishing: 3] [Article Influence: 2.0] [Reference Citation Analysis]
7 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]