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Article detail · 2025 · article

Professor X: Diagnosis and Treatment of Dermatological Diseases by Integration of Visual Diagnosis and Retrieval-Augmented Generation (RAG) Technologies

Journal IEEE Access
ISSN2169-3536
YÖKSİS OpenAlex Open access · gold
Year2025
Citations1OpenAlex
Percentile%70.0
FWCI0.461.00 = world average
Scopus (SJR)Q1
WoS (JCR)Q2

Data source split

  • YÖKSİSYÖKSİS article record
  • YÖKSİS venueIEEE ACCESS
  • Catalog match (ISSN)IEEE Access
  • OpenAlexOpenAlex enrichment (abstract, citations, topics)
  • Semantic Scholarcitation count (not merged with OpenAlex)

Abstract

OpenAlex English

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.

Topics

Citations

OpenAlex cited_by_count. Not a WoS or Scopus citation count; those sources have no separate column here.

1citationsOpenAlex · cited_by_count (cache / database)

Authors

1
  1. EMRE OLCA MALTEPE ÜNİVERSİTESİ 1