Professor X: Diagnosis and Treatment of Dermatological Diseases by Integration of Visual Diagnosis and Retrieval-Augmented Generation (RAG) Technologies
IEEE Access, cilt.13, ss.201246-201263, 2025 (SCI-Expanded, Scopus)
- Yayın Türü: Makale / Tam Makale
- Cilt numarası: 13
- Basım Tarihi: 2025
- Doi Numarası: 10.1109/access.2025.3636437
- Dergi Adı: IEEE Access
- Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Compendex, INSPEC, Directory of Open Access Journals
- Sayfa Sayıları: ss.201246-201263
- Anahtar Kelimeler: artificial intelligence, Dermatology, health technologies, image recognition, medical decision support, patient support systems, retrieval-augmented generation (RAG), skin disease diagnosis
- Maltepe Üniversitesi Adresli: Evet
Özet
Accurate and rapid diagnosis of dermatological diseases is important both in terms of improving the quality of life of individuals and increasing the efficiency of healthcare services. However, limited specialist access and delays in diagnostic processes are among the main problems encountered in dermatological care. In this study, "Professor X", an artificial intelligence-based dermatological diagnosis and support platform, is introduced. The system aims to provide services to both patients and medical professionals with a deep learning-based image recognition model and Retrieval-Augmented Generation (RAG) technology. Professor X offers a model that performs visual analysis of skin anomalies and can diagnose more than 30 skin diseases. Patients are provided with treatment recommendations and prevention strategies specific to their condition, while medical professionals are provided with constantly updated literature support, increasing diagnostic accuracy. This dynamic structure, integrated with weekly updates, ensures that the platform is supported by up-to-date medical information and optimizes decision-making processes. The system increases accessibility by bridging the gap between patient and professional users, speeds up diagnostic processes and ensures information accuracy. This approach, which democratizes the accessibility of healthcare services, sets a new standard in dermatological care and makes a significant contribution to the healthcare ecosystem.