6 papers
Privacy-Preserving Local Language Models for Longitudinal Data Retrieval in Chronic Dermatologic Disease: Implementation in Pemphigus Patients
Abdurrahim Yilmaz, AyÅe Esra Koku Aksu, Duygu Yamen +5
Chronic dermatologic diseases such as pemphigus require long-term follow-up, generating extensive longitudinal clinical documentation that is difficult to review comprehensively du…
Artefact-Aware Fungal Detection in Dermatophytosis: A Real-Time Transformer-Based Approach for KOH Microscopy
Rana Gursoy, Abdurrahim Yilmaz, Baris Kizilyaprak +5
Dermatophytosis is commonly assessed using potassium hydroxide (KOH) microscopy, yet accurate recognition of fungal hyphae is hindered by artefacts, heterogeneous keratin clearance…
DermaBench: A Clinician-Annotated Benchmark Dataset for Dermatology Visual Question Answering and Reasoning
Abdurrahim Yilmaz, Ozan Erdem, Ece Gokyayla +5
Vision-language models (VLMs) are increasingly important in medical applications; however, their evaluation in dermatology remains limited by datasets that focus primarily on image…
A Hierarchical Benchmark of Foundation Models for Dermatology
Furkan Yuceyalcin, Abdurrahim Yilmaz, Burak Temelkuran
Foundation models have transformed medical image analysis by providing robust feature representations that reduce the need for large-scale task-specific training. However, current…
An ensemble deep learning approach to detect tumors on Mohs micrographic surgery slides
Abdurrahim Yilmaz, Serra Atilla Aydin, Deniz Temur +7
Mohs micrographic surgery (MMS) is the gold standard technique for removing high risk nonmelanoma skin cancer however, intraoperative histopathological examination demands signific…
DermaSynth: Rich Synthetic Image-Text Pairs Using Open Access Dermatology Datasets
Abdurrahim Yilmaz, Furkan Yuceyalcin, Ece Gokyayla +8
A major barrier to developing vision large language models (LLMs) in dermatology is the lack of large image--text pairs dataset. We introduce DermaSynth, a dataset comprising of 92…