@article{article_1685185, title={AI-Powered Mobile Application for Early Detection of Dental Diseases Using Intraoral Imaging}, journal={Kocaeli Journal of Science and Engineering}, volume={8}, pages={133–146}, year={2025}, DOI={10.34088/kojose.1685185}, author={Güngör, Burçin and Yüzgeç, Uğur and Serin, Zafer}, keywords={Yapay Zeka, Mobil Sağlık Uygulaması, Diş Hastalıkları Tespiti, Ağız İçi Görüntüleme, Tıbbi Görüntü Analizi}, abstract={Oral health constitutes a fundamental component of overall well-being, with numerous systemic diseases, such as cardiovascular disorders, diabetes mellitus, and respiratory tract infections, being directly or indirectly associated with oral conditions. Delays in the diagnosis and treatment of dental diseases not only exacerbate oral complications but may also contribute to the progression of these systemic disorders, increasing both individual health burdens and the strain on healthcare systems. Recent advancements in artificial intelligence (AI), particularly in the domain of medical image analysis, have demonstrated significant potential in enhancing diagnostic accuracy and speed. Dentistry, which heavily relies on the visual assessment of intraoral structures, presents a promising field for the integration of AI-driven diagnostic tools. The use of AI can facilitate early detection of dental anomalies, enable timely intervention, and reduce the dependency on specialized clinical settings for initial screening. This study proposes the development of an AI-based mobile application that utilizes the ResNet50 model to detect common dental diseases through the analysis of intraoral photographs captured by users. Our model achieved an accuracy of 99.00%, a precision of 0.99, a recall of 0.99, and an F1-score of 0.99 on the test dataset. The application enables individuals to upload images of their oral cavity, receive automated diagnostic feedback, and, if necessary, schedule dental appointments based on the identified conditions. The integration of such a system into daily healthcare routines empowers users with accessible, real-time dental evaluations while supporting dental professionals in prioritizing patient care based on objective findings. By promoting early diagnosis and preventive care, the proposed solution not only contributes to improved oral and systemic health outcomes but also aligns with contemporary efforts to digitalize and optimize healthcare delivery through mobile and intelligent technologies.}, number={2}, publisher={Kocaeli Üniversitesi}