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Journal of Stomatology, Oral and Maxillofacial Surgery|March 8, 2024
Prediction of extraction difficulty for impacted maxillary third molars with deep learning approachDamla Torul, Hasan Akpinar, Ibrahim Sevki Bayrakdar, et al.
Polish Journal of Radiology|October 17, 2022
Segmentation of orbital and periorbital lesions detected in orbital magnetic resonance imaging by deep learning methodNevin Aydin, Suzan Saylisoy, Ozer Celik, et al.
International Journal of Computerized Dentistry|February 26, 2021
A pilot study of a deep learning approach to submerged primary tooth classification and detectionSecil Caliskan, Nuray Tuloglu, Ozer Celik, et al.
The Turkish Journal of Gastroenterology : the Official Journal of Turkish Society of Gastroenterology|October 20, 2004
Peutz-Jeghers syndrome: report of 6 cases in a family and management of polyps with intraoperative endoscopyOrhan Alimoğlu, Mustafa Sahin, Kivanç Cefle, et al.
Odontology|May 21, 2026
Multi-class anatomical landmark detection in periapical radiographs with deep learningCansu Buyuk, Alperen Saruhan, Fatma Yuce, et al.
Dento Maxillo Facial Radiology|July 18, 2024
Automatic deep learning detection of overhanging restorations in bitewing radiographsGuldane Magat, Ali Altındag, Fatma Pertek Hatipoglu, et al.
Children (Basel, Switzerland)|June 27, 2024
A Deep Learning Approach to Automatic Tooth Caries Segmentation in Panoramic Radiographs of Children in Primary Dentition, Mixed Dentition, and Permanent DentitionEsra Asci, Munevver Kilic, Ozer Celik, et al.
BMC Medical Imaging|July 2, 2025
Automated 3D segmentation of the hyoid bone in CBCT using nnU-Net v2: a retrospective study on model performance and potential clinical utilityIsmail Gümüssoy, Emre Haylaz, Suayip Burak Duman, et al.
Diagnostics (Basel, Switzerland)|July 12, 2025
Automatic Segmentation of the Infraorbital Canal in CBCT Images: Anatomical Structure Recognition Using Artificial IntelligenceIsmail Gumussoy, Emre Haylaz, Suayip Burak Duman, et al.
Nuclear Medicine Communications|March 2, 2022
Combined clinical and specific positron emission tomography/computed tomography-based radiomic features and machine-learning model in prediction of thymoma risk groupsElgin Ozkan, Kaan Orhan, Cigdem Soydal, et al.
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