Matvey Ezhov
Overview
Explore the profile of Matvey Ezhov including associated specialties, affiliations and a list of published articles.
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Articles
9
Citations
132
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Recent Articles
1.
Szabo V, Orhan K, Dobo-Nagy C, Veres D, Manulis D, Ezhov M, et al.
Diagnostics (Basel)
. 2025 Feb;
15(4).
PMID: 40002661
: Our study aimed to determine the accuracy of the artificial intelligence-based Diagnocat system (DC) in detecting periapical lesions (PL) on panoramic radiographs (PRs). 616 teeth were selected from 357...
2.
Szabo V, Szabo B, Orhan K, Veres D, Manulis D, Ezhov M, et al.
J Dent
. 2024 May;
147:105105.
PMID: 38821394
Objectives: This study aimed to assess the reliability of AI-based system that assists the healthcare processes in the diagnosis of caries on intraoral radiographs. Methods: The proximal surfaces of the...
3.
Amasya H, Alkhader M, Serindere G, Futyma-Gabka K, Aktuna Belgin C, Gusarev M, et al.
Diagnostics (Basel)
. 2023 Nov;
13(22).
PMID: 37998607
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...
4.
Orhan K, Aktuna Belgin C, Manulis D, Golitsyna M, Bayrak S, Aksoy S, et al.
Imaging Sci Dent
. 2023 Oct;
53(3):199-208.
PMID: 37799743
Purpose: The objective of this study was to evaluate the accuracy and effectiveness of an artificial intelligence (AI) program in identifying dental conditions using panoramic radiographs (PRs), as well as...
5.
Orhan K, Sanders A, Unsal G, Ezhov M, Misirli M, Gusarev M, et al.
Dentomaxillofac Radiol
. 2023 Aug;
52(7):20230141.
PMID: 37641960
Objectives: This study aims to evaluate the reliability of AI-generated STL files in diagnosing osseous changes of the mandibular condyle and compare them to a ground truth (GT) diagnosis made...
6.
Orhan K, Shamshiev M, Ezhov M, Plaksin A, Kurbanova A, Unsal G, et al.
Sci Rep
. 2022 Jul;
12(1):11863.
PMID: 35831451
This study aims to generate and also validate an automatic detection algorithm for pharyngeal airway on CBCT data using an AI software (Diagnocat) which will procure a measurement method. The...
7.
Ezhov M, Gusarev M, Golitsyna M, Yates J, Kushnerev E, Tamimi D, et al.
Sci Rep
. 2021 Nov;
11(1):22217.
PMID: 34754062
No abstract available.
8.
Ezhov M, Gusarev M, Golitsyna M, Yates J, Kushnerev E, Tamimi D, et al.
Sci Rep
. 2021 Jul;
11(1):15006.
PMID: 34294759
In this study, a novel AI system based on deep learning methods was evaluated to determine its real-time performance of CBCT imaging diagnosis of anatomical landmarks, pathologies, clinical effectiveness, and...
9.
Bayrakdar S, Orhan K, Bayrakdar I, Bilgir E, Ezhov M, Gusarev M, et al.
BMC Med Imaging
. 2021 May;
21(1):86.
PMID: 34011314
Background: The aim of this study was to evaluate the success of the artificial intelligence (AI) system in implant planning using three-dimensional cone-beam computed tomography (CBCT) images. Methods: Seventy-five CBCT...
10.
Orhan K, Bilgir E, Bayrakdar I, Ezhov M, Gusarev M, Shumilov E
J Stomatol Oral Maxillofac Surg
. 2020 Dec;
122(4):333-337.
PMID: 33346145
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....