A Kurt, DN Günaçar, FY Şılbır, Z Yeşil, İŞ Bayrakdar… - BMC Oral Health, 2024 - Springer
Background This study aims to evaluate the performance of a deep learning system for the evaluation of tooth development stages on images obtained from panoramic radiographs …
E Kaya, HG Gunec, SS Gokyay… - Journal of Clinical …, 2022 - meridian.allenpress.com
Objective: In this paper, we aimed to evaluate the performance of a deep learning system for automated tooth detection and numbering on pediatric panoramic radiographs. Study …
E Kaya, HG Gunec, KC Aydin, ES Urkmez… - Imaging science in …, 2022 - ncbi.nlm.nih.gov
Purpose The aim of this study was to assess the performance of a deep learning system for permanent tooth germ detection on pediatric panoramic radiographs. Materials and Methods …
E Kaya, HG Güneç, EŞ Ürkmez… - International Journal of …, 2023 - europepmc.org
Artificial intelligence (AI) based systems are used in dentistry to make the diagnostic process more accurate and efficient. The objective of this study was to evaluate the performance of a …
This study aimed to evaluate the performance of You Only Look Once (YOLO) v4 architecture for tooth detection on panoramic radiographs by calculating the sensitivity and …
Objective This study aimed to assess the performance of the deep learning (DL) model for automated tooth numbering in panoramic radiographs. Study Design The dataset of 500 …
FRS Teles, AC Mendes, AC Paiva, JDS Almeida… - … Conference on Wireless …, 2023 - Springer
Before a dental professional performs any procedure or diagnosis, they need to know the patient's dental arch. For that, it is common for them to ask the patient to take a panoramic …
T Zirek, MÜ Öziç, M Tassoker - Computers in Biology and Medicine, 2024 - Elsevier
Purpose Impacted teeth are abnormal tooth disorders under the gums or jawbone that cannot take their normal position even though it is time to erupt. This study aims to detect all …
Objectives We aimed to develop an artificial intelligence–based clinical dental decision- support system using deep-learning methods to reduce diagnostic interpretation error and …