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    Öğe
    Açılı Yerleştirilen Dental İmplantların Klinik Başarısı: Bir Uzun Süreli Gözlem Çalışması
    (2024) Ocak, Hakan; Çolpak, Halis Ali; Çolpak, Emine Dilara
    Amaç: Çenelerdeki çeşitli anatomik ve fizyolojik sınırlandır- malar sebebiyle diş eksikliklerinin tedavisinde, optimum bo- yutlarda dental implant yerleştirilmesi bazı durumlarda ek cerrahi işlemler gerçekleştirilmeden mümkün olmamaktadır. Alternatif tedavi seçeneği olan kısa implantların da klinik ba- şarılarının tartışmalı olması sebebiyle gününümüzde dental implantların açılı olarak yerleştirildiği tedavi seçenekleri gittik- çe popüler hale gelmektedir. Çalışmamızın amacı hastaların çenelerine açılı olarak yerleştirilen dental implantların klinik ve radyolojik özelliklerini belirlemek ve uzun dönem takipleri sonucunda klinik sağ kalımlarını değerlendirmektir. Gereç ve Yöntem: Hastalara açılı olarak yerleştirilen implant- ların yerleştirme tork değeri, ISQ değeri, yerleştirildiği bölge- nin varyasyonları ve eğim açıları kayıt edildi. Ortalama 21,7 ± 10,8 ay takipleri sonucu implant kayıpları ve implantın etrafın- daki boyun rezorbsiyonları tanımlayıcı ve demografik istatis- tiksel yöntemlerle değerlendirildi. Bulgular: Araştırmaya dahil edilen bireylerin 33’ü (%60) erkek ve 22’si (%40) ise kadın idi. İmplantların 17’si üst tuber, 24’ü üst premolar kanin ve 14’ü ise alt premolar kanin bölgesine yerleştirildi Yerleştirilen implantların; eğim açısı ortalama 47 ± 9,8 derece, implantın çapı ortalama 4,1 ± 0,4 mm, implant boyu ortalama 11,9 ± 1,7 mm olarak belirlendi. Bir vakada implant kaybı yaşanırken implantların ağızda kalma oranı %99 olarak belirlendi. Sonuç: Dişsiz çenelerin kısa sürede protetik rehabilitasyonu için implantların açılı olarak yerleştirildiği tedavi protokolü sayesinde, özellikle optimum boyutlarda dental implant yer- leştirilemeyen hastalarda öngörülebilir sonuçlarla başarılı bir tedavi olarak uygulanabilir.
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    Öğe
    Benchmarking Different Natural Language Processing Models for Their Responses to Queries on Toothsupported Fixed Dental Prostheses in Terms of Accuracy and Consistency
    (2025) Çolpak, Emine Dilara; Yilmaz, Deniz
    Aim: This study aimed to evaluate the accuracy and consistency of responses generated by four different natural language processing (NLP) models to the queries on tooth-supported fixed dental prostheses. Materials and Method: Twelve open-ended questions in Turkish were created and posed to four different NLPs according to the following models: OpenAI o3 (LRM-O), OpenAI GPT 4.5 (LLM-G), DeepSeek R1 (LRM-R), and DeepSeek V3 (LLM-V) with pre- prompts in the morning, afternoon, and evening. The responses were evaluated with a holistic rubric. For accuracy assessments, the Kruskal–Wallis H test was used. Consistency between the graders’ responses was assessed using the Brennan and Prediger coefficient and the Cohen kappa coefficient. Consistency among LLMs was assessed using the Fleiss kappa and Krippendorff alpha coefficients (p < 0.05). Results: There was no statistically significant difference in accuracy between the LRM-O, LLM-G, LRM-R, and LLM-V groups (p = 0.30). The respective accuracies of LRM-O, LLM-G, LRM-R, and LLM-V were 77.7%, 50%, 66.6%, and 77.7%. In addition, the consistency among LLMs was found to be almost perfect, whereas that of LRMs was substantial. Conclusion: Within the limitations of the study, LRMs and LLMs exhibited similar accuracy. However, the consistency among LLMs was higher than that of LRMs.
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    Öğe
    Chatgpt Vs. Google Gemini: Assessment of Performance Regarding the Accuracy and Repeatability of Responses to Questions in Implant-Supported Prostheses
    (2025) Yilmaz, Deniz; Çolpak, Emine Dilara
    Purpose: This study aimed to assess the accuracy and repeatability of the responses of different large language models (LLMs) to questions regarding implant-supported prostheses and assess the impact of pre-prompting and the time of day. Materials and Methods: A total of 12 open-ended questions related to implant-supported prostheses were generated. The content validity of questions was verified by a specialist. Following that, questions were posed to two different LLMs: ChatGPT-4.0 and Google Gemini (morning, afternoon, and evening; with and without pre-prompt). The responses were evaluated by two expert prosthodontists with a holistic rubric. The concordance between the graders’ responses and repeated responses by ChatGPT-4.0 and Gemini was calculated using the Brennan and Prediger coefficient, Cohen’s kappa coefficient, Fleiss’s kappa, and Krippendorff’s alpha coefficients. Kruskal-Wallis, Mann-Whitney U, and independent t-test, as well as ANOVA analyses, were used to compare the responses obtained in the implementations. Results: The results displayed that the accuracies of ChatGPT and Google Gemini were 34.7% and 17.4%, respectively. The implementation of pre-prompt significantly increased accuracy in Gemini (p = 0.026). No significant difference was found according to the time of day (morning, afternoon, or evening) or inter-week implementations. In addition, inter-rater reliability and repeatability displayed high levels of consistency. Conclusions: The use of pre-prompt positively affected accuracy and repeatability in both ChatGPT and Google Gemini. However, LLMs can still produce hallucinations. Therefore, LLMs may assist clinicians, but they should be aware of these limitations.
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    Öğe
    Effect of surface modifications of abutment screws on reverse Torque values: An in vitro study
    (Quintessence Publishing Co Inc, 2020) Çolpak, Emine Dilara; Gümüş, Hasan Önder
    Purpose: To investigate the reverse torque values of abutment screws subjected to various surface modifications. Materials and Methods: Sixty abutment screws were divided into two groups of 30 each: with thermomechanical cycling (240,000 cycles) and without thermomechanical cycling. Each group was then divided into three subgroups according to surface treatment: nontreated (NT, n = 10); anodic oxidation (AO, n = 10); and diamond-like carbon (DLC) coating (DLC, n = 10). All abutment screws were tightened to 30 Ncm using a digital torque meter. The reverse torque values of the abutment screws with and without thermomechanical cycling were then measured. The percentage of deviation (PERDEV) for reverse torque values was calculated. Two-way analysis of variance followed by Tukey Honest Significant Difference test were used for intergroup comparisons. Results: Significant differences were found among the PERDEV values of the groups based on thermomechanical cycling and surface treatment (P < .001 for each). A significant interaction was found between surface treatment and thermomechanical cycling (P < .001). Conclusion: Reverse torque values of abutment screws were found to be higher after surface treatments. The abutment screws with AO exhibited the lowest torque value loss in groups with and without thermomechanical cycling.