Evaluation of artificial intelligence for detecting impacted third molars on cone-beam computed tomography scans

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Orhan K., Bilgir E., Bayrakdar İ. Ş., Ezhov M., Gusarev M., Shumilov E.

JOURNAL OF STOMATOLOGY ORAL AND MAXILLOFACIAL SURGERY, vol.122, no.4, pp.333-337, 2021 (SCI-Expanded)

• Publication Type: Article / Article
• Volume: 122 Issue: 4
• Publication Date: 2021
• Doi Number: 10.1016/j.jormas.2020.12.006
• Journal Name: JOURNAL OF STOMATOLOGY ORAL AND MAXILLOFACIAL SURGERY
• Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus, EMBASE, MEDLINE
• Page Numbers: pp.333-337
• Keywords: Impacted third molar, Mandibular canal, Artificial intelligence, Deep learning, CONVOLUTIONAL NEURAL-NETWORK, TEETH, CLASSIFICATION, DIAGNOSIS
• Eskisehir Osmangazi University Affiliated: Yes

Abstract

Purpose: The aim of this study was to evaluate the diagnostic performance of artificial intelligence (AI) application evaluating of the impacted third molar teeth in Cone-beam Computed Tomography (CBCT) images.