4 papers
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…