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

Orhan, Kaan; Bilgir, Elif; Bayrakdar, Ibrahim Sevki; Ezhov, Matvey; Gusarev, Maxim; Shumilov, Eugene

Orhan, Kaan; Bilgir, Elif; Bayrakdar, Ibrahim Sevki; Ezhov, Matvey; Gusarev, Maxim; Shumilov, Eugene.

Afiliación

Orhan K; Department of Oral and Maxillofacial Radiology, Faculty of Dentistry, Ankara University, Ankara, Turkey; Ankara University Medical Design Application and Research Center (MEDITAM), Ankara, Turkey.
Bilgir E; Department of Oral and Maxillofacial Radiology, Faculty of Dentistry, Eskisehir Osmangazi University, Eskisehir, Turkey.
Bayrakdar IS; Department of Oral and Maxillofacial Radiology, Faculty of Dentistry, Eskisehir Osmangazi University, Eskisehir, Turkey. Electronic address: ibrahimsevkibayrakdar@gmail.com.
Ezhov M; Diagnocat, Inc, San Francisco, USA.
Gusarev M; Diagnocat, Inc, San Francisco, USA.
Shumilov E; Diagnocat, Inc, San Francisco, USA.

J Stomatol Oral Maxillofac Surg ; 122(4): 333-337, 2021 09.

Article en En | MEDLINE | ID: mdl-33346145

Asunto(s)

Tercer Molar; Diente Impactado; Inteligencia Artificial; Tomografía Computarizada de Haz Cónico; Humanos; Tercer Molar/diagnóstico por imagen; Estudios Retrospectivos; Diente Impactado/diagnóstico por imagen

Palabras clave

Artificial intelligence; Deep learning; Impacted third molar; Mandibular canal

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Texto completo: 1 Base de datos: MEDLINE Asunto principal: Diente Impactado / Tercer Molar Tipo de estudio: Observational_studies Idioma: En Revista: J Stomatol Oral Maxillofac Surg Año: 2021 Tipo del documento: Article

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