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    Artificial Intelligence-Based Detection and Numbering of Dental Implants on Panoramic Radiographs
    (Wiley, 2025) Balel, Yunus; Sagtas, Kaan; Teke, Fatih; Kurt, Mehmet Ali
    ObjectivesThis study aimed to develop an artificial intelligence (AI)-based deep learning model for the detection and numbering of dental implants in panoramic radiographs. The novelty of this model lies in its ability to both detect and number implants, offering improvements in clinical decision support for dental implantology.Materials and MethodsA retrospective dataset of 32 585 panoramic radiographs, collected from patients at Sivas Cumhuriyet University between 2014 and 2024, was utilized. Two deep-learning models were trained using the YOLOv8 algorithm. The first model classified the regions of the jaw to number the teeth and identify implant regions, while the second model performed implant segmentation. Performance metrics including precision, recall, and F1-score were used to evaluate the model's effectiveness.ResultsThe implant segmentation model achieved a precision of 91.4%, recall of 90.5%, and an F1-score of 93.1%. For the implant-numbering task, precision ranged from 0.94 to 0.981, recall from 0.895 to 0.956, and F1-scores from 0.917 to 0.966 across various jaw regions. The analysis revealed that implants were most frequently located in the maxillary posterior region.ConclusionsThe AI model demonstrated high accuracy in detecting and numbering dental implants in panoramic radiographs. This technology offers the potential to reduce clinicians' workload and improve diagnostic accuracy in dental implantology. Further validation across more diverse datasets is recommended to enhance its clinical applicability.Clinical RelevanceThis AI model could revolutionize dental implant detection and classification, providing fast, objective analyses to support clinical decision-making in dental practices.
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    Can ChatGPT-4o provide new systematic review ideas to oral and maxillofacial surgeons?
    (Elsevier Masson s.r.l., 2024) Balel, Yunus; Zogo, Atakan; Yıldız, Serkan; Tanyeri, Hakkı
    Objective: This study aims to evaluate the capacity of ChatGPT-4o to generate new systematic review ideas in the field of oral and maxillofacial surgery. The data obtained from this study will provide evidence-based information to oral and maxillofacial surgeons regarding the academic use of GPT-4o. Materials and methods: ChatGPT-4o was asked to provide four previously unpublished systematic review ideas each for the topics of impacted third molars, dental implants, orthognathic surgery, and temporomandibular disorders. A literature search was conducted in the PubMed database to check if the ideas generated by GPT-4o had been previously published, and the search results were compared with the ideas generated by the AI. Results: The PubMed database search resulted in a total of 871 publications, with 37 publications found to be related to the topics generated by GPT-4o after the first and second screening. Out of the 16 publication ideas generated by GPT-4o, 9 (56.25 %) were determined to be previously unexplored according to the PubMed database search. There was no statistically significant relationship between the presence of ChatGPT's suggestions in PubMed and the subject areas of the studies. Conclusion: ChatGPT-4o has a high potential to be used as a valuable tool for suggesting systematic review topics in oral and maxillofacial surgery. Additionally, this tool can assist researchers not only in proposing publication ideas but also in developing the methodology of the study. © 2024 Elsevier Masson SAS
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    Comorbidity of Body Dysmorphic Disorder and Obsessive-Compulsive Disorder in Orthognathic Surgery Patients
    (2024) Maden, Abdulsamed; Akbulut, Nihat; Balel, Yunus
    Objective: Body dysmorphic disorder (BDD) is a mental health disorder in which a person believes that their actual physical features appear worse than they truly are. The aim of this study is to examine the presence of BDD and its comorbidity with anxiety, depression, and obsessive-compulsive disorder (OCD) in patients with planned orthognathic surgery for dentofacial deformities. Methods: In this study conducted on patients scheduled for orthognathic surgery, the presence of BDD, OCD, depression, anxiety, and stress was determined by administering the Florida Obsessive-Compulsive Inventory (FOCI), Depression, Anxiety, and Stress Scale-21 (DASS-21), and Body Image Disturbance Questionnaire (BIDQ) prior to the surgery. An independent samples t-test evaluated differences between group means, Pearson’s correlation coefficient demonstrated the linear relationship between two variables, and the chi-square test assessed the relationship between two categorical variables. A p-value below 0.05 was deemed statistically significant. A total of 108 patients were included in the study, with 54 patients Class 2 and 54 patients Class 3. Results: BIDQ, FOCI, depression, anxiety, and stress, males showed statistically significant higher results compared to females (p <0.05). There were no statistically significant differences in BIDQ, FOCI, depression, and stress between Class 2 and Class 3 patients (p>0.05). Of the 108 patients included in the study, a total of 20.4% (n=22) were found to be BDD positive. Among the female patients, 10% (n=6) were BDD positive, while among the male patients, 33.3% (n=16) were BDD positive. When evaluated in terms of skeletal classification, 14.8% (n=8) of Class 2 patients were BDD positive, while 25.9% (n=14) of Class 3 patients were BDD positive. Conclusions: Surgeons performing orthognathic surgery should be familiar with common and often severe body image disturbances. When evaluating patients seeking orthognathic surgery, their psychological conditions should be carefully considered.
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    Does Laser-LED Photobiomodulation Therapy Alleviate Swlling, Pain, and Trismus Following Impacted Third Molar Extraction?
    (Sivas Cumhuriyet Üniversitesi, 2025) Şen, Esengül; Balel, Yunus
    Objectives: The aim of this study is to examine the effectiveness of a single-session application of laser-LED based photobiomodulation therapy (PBMT) (using a 904 nm GaAlAs infrared laser and a 650 nm InGaAIP LED) on pain, edema, trismus, and the quality of life of patients following impacted mandibular third molar extraction. Materials and Methods: The study included patients whose impacted mandibular third molars were to be extracted for prophylactic purposes. The patients were divided into two groups as the PBMT group and the placebo control group. Pain, swelling, maximum mouth opening, and quality of life parameters of the patients were evaluated. Results: The study included a total of 36 patients, with 15 in the placebo control group and 21 in the laser group. Pain, maximum mouth opening, and edema measurements changed statistically after surgery (P.05). While no statistically significant difference was found between the groups in terms of isolation, eating-drinking, sleep, and physical appearance, the placebo control group was significantly less affected in terms of speech changes compared to the laser group (P = .019). Conclusions: Further randomized controlled clinical trials are required to determine the optimal wavelength and dose for PBMT in reducing morbidity after impacted wisdom tooth surgery.
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    ScholarGPT's performance in oral and maxillofacial surgery
    (Elsevier, 2025) Balel, Yunus
    Objective: The purpose of this study is to evaluate the performance of Scholar GPT in answering technical questions in the field of oral and maxillofacial surgery and to conduct a comparative analysis with the results of a previous study that assessed the performance of ChatGPT. Materials and Methods: Scholar GPT was accessed via ChatGPT (www.chatgpt.com) on March 20, 2024. A total of 60 technical questions (15 each on impacted teeth, dental implants, temporomandibular joint disorders, and orthognathic surgery) from our previous study were used. Scholar GPT's responses were evaluated using a modified Global Quality Scale (GQS). The questions were randomized before scoring using an online randomizer (www.randomizer.org). A single researcher performed the evaluations at three different times, three weeks apart, with each evaluation preceded by a new randomization. In cases of score discrepancies, a fourth evaluation was conducted to determine the final score. Results: Scholar GPT performed well across all technical questions, with an average GQS score of 4.48 (SD=0.93). Comparatively, ChatGPT's average GQS score in previous study was 3.1 (SD=1.492). The Wilcoxon Signed-Rank Test indicated a statistically significant higher average score for Scholar GPT compared to ChatGPT (Mean Difference = 2.00, SE = 0.163, p < 0.001). The Kruskal-Wallis Test showed no statistically significant differences among the topic groups (x(2) = 0.799, df= 3, p = 0.850, epsilon(2) = 0.0135). Conclusion: Scholar GPT demonstrated a generally high performance in technical questions within oral and maxillofacial surgery and produced more consistent and higher-quality responses compared to ChatGPT. The findings suggest that GPT models based on academic databases can provide more accurate and reliable information. Additionally, developing a specialized GPT model for oral and maxillofacial surgery could ensure higher quality and consistency in artificial intelligence-generated information. (c) 2024 Elsevier Masson SAS. All rights are reserved, including those for text and data mining, AI training, and similar technologies.
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    The most influential publications in oral and maxillofacial surgery over the past decade
    (Elsevier Masson s.r.l., 2024) Balel, Yunus
    Objective: Reliable metrics are needed to measure the impact of academic publications in order to fully understand and evaluate the contributions of articles published in the field of oral and maxillofacial surgery(OMFS). The aim was to identify and analyze the top 100 articles each year, with the highest Field-Weighted Citation Impact(FWCI) and citation counts, in the field of OMFS over the past decade, totaling 1,000 articles. Materials and Methods: The research was conducted on April 20, 2024, using the Scopus database. It identified the top 100 articles each year with the highest FWCI from the top six journals with the highest metric scores in OMFS, totaling 1,000 articles. The citation counts of these publications in Google Scholar were also recorded. The predictor variable was the articles. The primary outcome variable was the FWCI value, while the secondary outcome variable was the number of citations. The covariates were the journals in which the articles were published, the publication year, the type of document, the type of access policy, and the subject of the research. Results: There was a weak positive correlation between FWCI and citation count(rho = 0.083, P =.009). All covariates significantly affected FWCI(P <.005), while all but access policy significantly affected citation count(P =.167). The highest average FWCI(6.31 ± 5.51) was observed in the Journal of Stomatology, Oral and Maxillofacial Surgery(JSOMS), and the highest citation count was found in the Journal of Oral and Maxillofacial Surgery(JOMS)(61.5 ± 126.4). Orthognathic Surgery and Dentofacial Deformities were the scientific fields with the most publications(14 %). COVID-19 and Artificial Intelligence had the highest FWCI(8.65 ± 10.98 and 7.68 ± 6.42, respectively). MRONJ had the highest average citation count(88.6 ± 254). Conclusion: This study demonstrates that using both FWCI and citation count metrics can more accurately assess the impact of academic publications in the field of OMFS. These findings can serve as a guide for future research and contribute to strategic decisions aimed at improving clinical practices and patient care. © 2024 Elsevier Masson SAS