JHSM
Journal of Health Sciences and Medicine

Journal of Health Sciences and Medicine (JHSM) is an unbiased, peer-reviewed, and open access international medical journal. The Journal publishes interesting clinical and experimental research conducted in all fields of medicine, interesting case reports, and clinical images, invited reviews, editorials, letters, comments, and related knowledge.

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Original Article
AI-based determination of Kennedy classification and modification spaces on panoramic radiographs
Abstract
Aims: The aim of this study is to automatically perform tooth segmentation, FDI (Fédération Dentaire Internationale) tooth numbering, and the Artificial Intelligence (AI)-based determination of Kennedy classification and its modifications using images obtained from panoramic dental radiographs. The study aims to help clinical decision support processes in prosthetic dentistry. Methods: The U-Net architecture was used for pixel-level tooth segmentation on panoramic dental radiographs, and different pre-trained encoder backbones were compared. Segmentation performance was evaluated using the Dice Similarity Coefficient and Intersection over Union metrics. The outputs of the best-performing model were integrated with the FDI tooth numbering system to automatically determine Kennedy classification and modification areas. Results: The results were evaluated by two clinicians specialized in prosthetic dentistry. Findings the U-Net model with the ResNet34 encoder demonstrated higher and more balanced segmentation performance compared to the other architectures. Statistical analyses revealed that the ResNet34 model was significantly superior to the other encoder configurations used in the study (p

Keywords : Deep learning, prosthodontics, Kennedy classification, dental image segmentation

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Article available in :
Volume 9, Issue 3, 2026
Page : 627-637
https://doi.org/10.32322/jhsm.1870007
Article Information
Received : 23 Oca 2026
Accepted : 07 Nis 2026
Published : 19 May 2026
Corresponding Author :

Aliye İpek Kuşçu: Department of Prosthodontics, Faculty of Dentistry, Yozgat Bozok University, Yozgat, Turkiye

[email protected]
Citation : Kuşçu Aİ, Ortataş FN, Dolar A, Kuşçu S. AI-based determination of Kennedy classification and modification spaces on panoramic radiographs. J Health Sci Med. 2026;9(3):627-637. doi:10.32322/jhsm.1870007

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