DSpace Arşivi :: Ana Sayfa

İstanbul Gelişim Üniversitesi Kurumsal Açık Erişim Arşivi

DSpace@Gelişim, İstanbul Gelişim Üniversitesi tarafından doğrudan ve dolaylı olarak yayınlanan; kitap, makale, tez, bildiri, rapor, araştırma verisi gibi tüm akademik kaynakları uluslararası standartlarda dijital ortamda depolar, Üniversitenin akademik performansını izlemeye aracılık eder, kaynakları uzun süreli saklar ve yayınların etkisini artırmak için telif haklarına uygun olarak Açık Erişime sunar.

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Can Artificial Intelligence Chatbots (ChatGPT, DeepSeek, Copilot, and Claude) Accurately Inform Patients About Subperiostal Jaw Implants?
(B. C. Decker, 2026) Gaş, Selin; Paksoy, Tuğçe; Çeçen, Cemre; Altınay Uncu, Sevda; Selvi, Fırat
Background: Severe jawbone atrophy often limits the use of conventional dental implants. Modern 3D imaging and CAD/ CAM technologies have revitalized subperiosteal implants as a customized alternative for these challenging cases. As AI chatbots (ChatGPT, Claude, DeepSeek, and Copilot) increasingly serve as patient information tools, evaluating the accuracy and clarity of their explanations about such complex procedures has become essential. Objective: This study aimed to evaluate the accuracy, reliability, readability, actionability, understandability, and practical usefulness of responses provided by AI chatbots to patient questions about subperiosteal jaw implants. Methods: The authors evaluated 4 AI-based chatbots (ChatGPT, DeepSeek, Copilot, and Claude) by submitting frequently asked questions on subperiosteal jaw implants in independent sessions to avoid data leakage. Responses were compiled, duplicates removed, and refined for clarity. Two independent experts assessed the outputs using validated tools: accuracy (5-point Likert), reliability (CLEAR criteria), quality (mGQS), readability (FRE, FKGL), usefulness (4-point scale), and understandability/actionability (PEMAT). Results: DeepSeek, Claude, and ChatGPT produced more understandable, actionable, and higher-quality responses than CoPilot, with DeepSeek performing the best overall. Across all models, clarity, mGQS, and accuracy were strongly aligned, while usefulness was inversely related. Readability and actionability-understandability correlations showed consistent patterns, with the strongest positive link observed in DeepSeek. Conclusion: AI chatbots, such as DeepSeek, Claude, and ChatGPT, can provide accurate and understandable in formation about the subperiosteal jaw implants, though practical guidance and readability remain limited. Domain-specific training and integration with authoritative dental resources may enhance their clinical utility and patient education potential.
Shear bond strength of adhesive systems on PEEK, PEKK, and fiber-reinforced composites: an in vitro study
(BioMed Central Ltd, 2026) Bilgi Özyetim, Esra; Al-Zamily, Mohammed Sajid; Öztürk Yeşilırmak, Sevda
Background Strong and durable bonding between composite resins and high-performance polymers (HPPs) is difficult to achieve because of HPPs’ low surface energy and chemical inertness, which limit their clinical applicability. This in vitro study aimed to evaluate the shear bond strength (SBS) between a composite resin and HPPs using different adhesive systems. Methods Disc-shaped specimens of polyetheretherketone (PEEK), polyetherketoneketone (PEKK), and fiberreinforced composite (FRC) (n=50 per group) were fabricated and sandblasted with 50 μm aluminum oxide (Al₂O₃) particles. Surface roughness (Ra) was measured using a profilometer, and surface topography was evaluated using scanning electron microscopy (SEM). Each polymer group was divided into five subgroups (n=10) according to the adhesive system used: Scotchbond Universal, G-Premio BOND, Tokuyama Universal Bond, visio.link, and PEKK Bond. Following the adhesive application, a composite resin was applied to each specimen surface and then lightpolymerized. All specimens were subjected to thermocycling for 5,000 cycles. After thermocycling, SBS was measured using a universal testing machine. Data were analyzed using a two-way and one-way ANOVA with Tukey’s HSD test (α=0.05). Results FRC demonstrated the highest Ra and SBS values, followed by PEKK and PEEK. The 10-methacryloyloxydecyldihydrogenphosphat (MDP) - and silane-containing adhesive (Scotchbond Universal) showed significantly higher SBS values compared to the other adhesive systems. Cohesive failure represented the predominant type of failure in most groups. Conclusions Universal adhesives containing functional monomers such as MDP and silane may provide reliable bonding to HPP materials after airborne-particle abrasion. Within the limitations of this in vitro study, these findings support the clinical use of universal adhesives for chairside repair and veneering procedures of HPP-based restorations. Additionally, the selection of appropriate surface conditioning and adhesive protocols may help improve the longevity and predictability of polymer-based prosthetic restorations.
Domain-Specific vs. General-Purpose Large Language Models in Orthodontics: A Blinded Comparison of AlimGPT, GPT-4o, Gemini, and Llama
(MDPI AG, 2026) Aksakallı, Sertaç; Giray, Bilgin; Temel, Çağrı
Objective: The application of artificial intelligence (AI) in orthodontics has evolved rapidly in recent years, encompassing areas such as diagnosis, treatment planning, and patient management, and AlimGPT is an AI-based tool that provides treatment options based on data and algorithms. Methods: Fourteen different orthodontic questions were asked to each model, and answers were analyzed. This study aimed to compare AlimGPT with GPT-4o, Gemini, and Llama using standardized tests to evaluate the quality of information provided, including the Likert scale, modified DISCERN (mDISCERN), and modified Global Quality Score (mGQS). Results: Significant differences were detected for reliability (χ 2 = 15.267, p = 0.0016) and usefulness (χ 2 = 20.557, p = 0.0001). Post hoc tests showed AlimGPT > Gemini and Llama for reliability and AlimGPT > GPT-4o, Gemini, and Llama for usefulness. mDISCERN was significant overall (χ 2 = 11.047, p = 0.0115), but no pairwise contrast met adjusted significance; mGQS showed no significant differences (χ 2 = 7.071, p = 0.0697). Inter-rater agreement was moderate-to-good for reliability (ICC = 0.710, 95% CI 0.60–0.80) and usefulness (ICC = 0.729, 95% CI 0.63–0.82), moderate for mGQS (ICC = 0.596, 95% CI 0.47–0.71), and poor-to-moderate for mDISCERN (ICC = 0.435, 95% CI 0.30–0.58). Conclusions: In this blinded, within-subjects experiment, the domain-specific model (AlimGPT) received higher clinician ratings for usefulness and, for reliability, exceeded two general baselines. Differences in mGQS were not detected. Expanding the number of raters, increasing item diversity or integrating updated baselines would be beneficial.
Evaluation Of Parotid And Submandibular Salivary Glands By Ultrasonography in Patients Using Antidepressants: A Case Control Study
(BioMed Central Ltd, 2026) Tanrıverdi, Semih; Yeşiltepe, Selin
Background: Antidepressants are widely prescribed group of medications frequently associated with xerostomia. Although alterations in salivary flow among antidepressant users have been extensively investigated, there is a paucity of data regarding the structural and vascular ultrasonographic characteristics of the major salivary glands. This study aimed to evaluate the echogenicity, parenchymal structure, margin characteristics, blood supply characteristics, and dimensions of the parotid and submandibular glands in antidepressant users compared with systemically healthy controls using ultrasonography (USG). Methods: In this study, both right and left parotid and submandibular salivary glands of 102 individuals (51 healthy and 51 antidepressant users) were examined by USG. Data normality was evaluated using the Kolmogorov–Smirnov test. Group comparisons were performed using independent samples t-tests or Mann–Whitney U tests, as appropriate, and categorical variables were analyzed using the chi-square test. A p-value < 0.05 was considered statistically significant. Results: There is no significant differences between antidepressant users and healthy individuals in terms of echogenicity, parenchymal structure, margin and blood supply characteristics of the submandibular and parotid salivary glands. However, the mean supero-inferior dimension of the right submandibular gland was significantly higher in the patient group than in the control group. The median medio-lateral dimension of the left submandibular gland was significantly lower in patients compared with controls. Additionally, the mean medio-lateral dimensions of both the right and left parotid glands were significantly lower in the patient group than in the control group. Conclusions: The ultrasonographic appearance of the major salivary glands did not differ significantly between antidepressant users and healthy controls in terms of tissue characteristics and vascularity, despite limited dimensional differences. These findings suggest that antidepressant use does not markedly alter the ultrasonographic appearance of the salivary glands. Further studies with larger sample sizes, incorporating salivary flow measurements and elastography, are warranted to elucidate the functional and biomechanical effects of antidepressant use on the salivary glands.
Istanbul Gelişim University Faculty of Sports Sciences: Monthly E-Bulletin (June 2026)
(İstanbul Gelişim Üniversitesi / Istanbul Gelisim University, 2026) Istanbul Gelişim University Faculty of Sports Sciences
İSTANBUL GELİSİM UNİVERSİTY HOSTS "AL AND THE FUTURE OF THE SPORTS INDUSTRY” SYMPOSİUM SUCCESSFULLY HELD The "Al and the Future of the Sports Industry" Symposium, organized in collaboration with the Faculty of Sport Sciences at Istanbul Gelisim University and the Turkish Bodybuilding, Fitness and Armwrestling Federation, was held on June 3-4, 2026, at Istanbul Gelisim University with great participation. Bringing together academicians, industry representatives, coaches, sports administrators and students under one roof, the symposium addressed the transformation of artificial intelligence technologies in sports sciences and the sports industry from a scientific perspective.