Sevda Kurt-Bayrakdar, Mehmet Uğurlu, Muhammet Burak Yavuz, Nichal Sali, İbrahim Şevki Bayrakdar, Özer Çelik, Oğuz Köse, Arzu Beklen, Bilge Cansu Uzun Saylan, Rohan Jagtap, Kaan Orhan
OBJECTIVES: This study aimed to develop an artificial intelligence (AI) model that can determine automatic tooth numbering, frenulum attachments, gingival overgrowth areas, and gingival inflammation signs on intraoral photographs and to evaluate the performance of this model. METHOD AND MATERIALS: A total of 654 intraoral photographs were used in the study (n = 654). All photographs were reviewed by three periodontists, and all teeth, frenulum attachment, gingival overgrowth areas, and gingival inflammation signs on photographs were labeled using the segmentation method in a web-based labeling software...
September 19, 2023: Quintessence International