Evaluation of a Decision Support System Developed with Deep Learning Approach for Detecting Dental Caries with Cone-Beam Computed Tomography Imaging

This study aims to investigate the effect of using an artificial intelligence (AI) system (Diagnocat, Inc., San Francisco, CA, USA) for caries detection by comparing cone-beam computed tomography (CBCT) evaluation results with and without the software. 500 CBCT volumes are scored by three dentomaxil...

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Hlavní autoři:	Hakan Amasya, Mustafa Alkhader, Gözde Serindere, Karolina Futyma-Gąbka, Ceren Aktuna Belgin, Maxim Gusarev, Matvey Ezhov, Ingrid Różyło-Kalinowska, Merve Önder, Alex Sanders, Andre Luiz Ferreira Costa, Sérgio Lúcio Pereira de Castro Lopes, Kaan Orhan
Médium:	Artigo
Jazyk:	Inglês
Vydáno:	MDPI AG 2023-11-01
Edice:	Diagnostics
Témata:	dental caries cone-beam computed tomography machine learning decision support systems
On-line přístup:	https://www.mdpi.com/2075-4418/13/22/3471
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