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

Orhan, Kaan; Bilgir, ELİF; Bayrakdar, İBRAHİM; Ezhov, Matvey; Gusarev, Maxim; Shumilov, Eugene

doi:10.1016/j.jormas.2020.12.006

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

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

JOURNAL OF STOMATOLOGY ORAL AND MAXILLOFACIAL SURGERY, cilt.122, sa.4, ss.333-337, 2021 (SCI-Expanded, Scopus)

Yayın Türü: Makale / Tam Makale
Cilt numarası: 122 Sayı: 4
Basım Tarihi: 2021
Doi Numarası: 10.1016/j.jormas.2020.12.006
Dergi Adı: JOURNAL OF STOMATOLOGY ORAL AND MAXILLOFACIAL SURGERY
Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, EMBASE, MEDLINE
Sayfa Sayıları: ss.333-337
Anahtar Kelimeler: Impacted third molar, Mandibular canal, Artificial intelligence, Deep learning, CONVOLUTIONAL NEURAL-NETWORK, TEETH, CLASSIFICATION, DIAGNOSIS
Eskişehir Osmangazi Üniversitesi Adresli: Evet

Özet

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.