AHMET YAGCI

Prof. Dr. AHMET YAGCI

orcid

Research Focus & Metrics

Academic Career Length

17Years (2010-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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1 January 2022 in Dental Press Journal of Orthodontics
Verified
Journal Article
Open access
GÇGökhan Çoban
Gökhan Çoban
TÖTANER ÖZTÜRK
TANER ÖZTÜRK
NHNizami Hashimli
Nizami Hashimli
AYAHMET YAGCI
AHMET YAGCI
Objective: The aim of this study was to compare the measurements performed with digital manual (DM) cephalometric analysis and automatic cephalometric analysis obtained from an online artificial intelligence (AI) platform, according to different sagittal skeletal malocclusions. Methods: Cephalometric radiographs of 105 randomly selected individuals (mean age: 17.25 ± 1.87 years) were included in this study. Dolphin Imaging software was used for DM cephalometric analysis, and the WebCeph platform was used for AI-based cephalometric analysis. In total, 10 linear and 12 angular measurements were evaluated. The paired t-test, one-way ANOVA test, and intraclass correlation coefficient tests were used to evaluate the differences between the two methods. The level of statistical significance was set at p< 0.05. Results: Except for SNB, NPog, U1.SN, U1.NA, L1-APog, I/I, and LLE parameters, all other parameters presented significant differences between the two methods (p< 0.05). While there was no difference (p> 0.05) in both SNA and SNB measurements between the two methods in the Class I malocclusion group, there was a difference between both methods in the Class II malocclusion group. Meanwhile, only the SNA in the Class III malocclusion group was different (p< 0.05). The ANB angle differed significantly in all three malocclusion groups. For both methods, all parameters except CoA and CoGn were found to have good correlation. Conclusion: Although significant differences were detected in some measurements between the two cephalometric analysis methods, not all differences were clinically significant. The AI-based cephalometric analysis method needs to be developed for more specific malocclusions.

1 January 2019 in American Journal of Orthodontics and Dentofacial Orthopedics
Verified
Journal Article
Closed access
SASibel Akbulut
Sibel Akbulut
AYAHMET YAGCI
AHMET YAGCI
AYArzu Hanim Yay
Arzu Hanim Yay
BYBetul Yalcin
Betul Yalcin

16 March 2011 in Orthodontics & Craniofacial Research
Verified
Journal Article
Closed access
PDF file
TUT Uysal
T Uysal
SGS Gorgulu
S Gorgulu
AYAHMET YAGCI
AHMET YAGCI
YKY Karslioglu
Y Karslioglu
OGO Gunhan
O Gunhan
DSD Sagdic
D Sagdic

1 March 2016 in American Journal of Orthodontics and Dentofacial Orthopedics
Verified
Journal Article
Closed access
AYAHMET YAGCI
AHMET YAGCI
YKYasemin Nur Korkmaz
Yasemin Nur Korkmaz
SBSuleyman Kutalmis Buyuk
Suleyman Kutalmis Buyuk
FYFiliz Yagci
Filiz Yagci
AAAykan Onur Atilla
Aykan Onur Atilla

1 July 2013 in American Journal of Orthodontics and Dentofacial Orthopedics
Verified
Journal Article
Closed access
AYAHMET YAGCI
AHMET YAGCI
TUTancan Uysal
Tancan Uysal
KDKevser Kurt Demirsoy
Kevser Kurt Demirsoy
DPDuygu Percin
Duygu Percin

28 November 2025 in BMC Oral Health
Verified
Journal Article
Open access
PDF file
MEMerve Ece Erdem
Merve Ece Erdem
GÇGökhan Çoban
Gökhan Çoban
TÖTANER ÖZTÜRK
TANER ÖZTÜRK
AYAHMET YAGCI
AHMET YAGCI
IYİbrahim Yavuz
İbrahim Yavuz
AAAlper Alkan
Alper Alkan
Orthognathic surgery is a well-established method for correcting skeletal dentofacial deformities. Despite its widespread application, large-scale data des