Deep learning for determining the difficulty of endodontic treatment: a pilot study

• Main Authors: Hamed Karkehabadi (Author), Elham Khoshbin (Author), Nikoo Ghasemi (Author), Amal Mahavi (Author), Hossein Mohammad-Rahimi (Author), Soroush Sadr (Author)
• Format: Book
• Published: BMC, 2024-05-01T00:00:00Z.
• Subjects: article
• Online Access: Connect to this object online.

Abstract Background To develop and validate a deep learning model for automated assessment of endodontic case difficulty from periapical radiographs. Methods A dataset of 1,386 periapical radiographs was compiled from two clinical sites. Two dentists and two endodontists annotated the radiographs fo...