@article{article_1925352, title={Comparative Agreement of the Online Implant Disease Risk Assessment (IDRA) Tool, ChatGPT and DeepSeek in Peri-implant Disease Risk Classification: A 500-Case Scenario Study}, journal={Akdeniz Diş Hekimliği Dergisi}, volume={5}, pages={11–18}, year={2026}, DOI={10.62268/add.1925352}, url={https://izlik.org/JA36EW98GS}, author={Canpolat, Berfin and Yıldız, Yiğitcan and Zeylek, Muhammed Talha and Ercan, Esra}, keywords={yapay zeka, Chat-GPT, DeepSeek, risk değerlendirmesi, dental implantlar}, abstract={Objectives The aim of this study was to evaluate the level of agreement between an online Implant Disease Risk Assessment (IDRA) tool and large language models in classifying patients into low, moderate, and high peri-implant disease risk categories. Material and Methods A total of 500 standardized implant case scenarios were generated based on established different clinical scenarios. Each scenario included clinical variables such as age, number of teeth and implants, probing depth, bleeding on probing, bone loss, history of periodontitis, and maintenance compliance. All cases were entered into IDRA (perio-tools.com), ChatGPT, and DeepSeek using an identical input format. Risk classifications were recorded as low, moderate, or high. Agreement between systems was assessed using linearly weighted Cohen’s kappa statistics. Results IDRA classified 95.8% of cases as high risk, whereas ChatGPT and DeepSeek showed more heterogeneous distributions (72.4% and 88.6% high risk, respectively). Agreement between ChatGPT and DeepSeek was moderate (κw = 0.442), while higher agreement was observed between IDRA and DeepSeek (κw = 0.532). The lowest agreement was found between IDRA and ChatGPT (κw = 0.258). Conclusion Large language models show variable agreement with structured peri-implant risk assessment systems. Differences in classification tendencies and class distribution may influence agreement outcomes. These findings reflect differences in classification pattern rather than diagnostic accuracy or clinical validity. Further validation using clinical data is required before any potential clinical application.}, number={1}, organization={The authors declared that this study has received no financial support.}