Paper ID: 2405.18004

SkinCAP: A Multi-modal Dermatology Dataset Annotated with Rich Medical Captions

Juexiao Zhou, Liyuan Sun, Yan Xu, Wenbin Liu, Shawn Afvari, Zhongyi Han, Jiaoyan Song, Yongzhi Ji, Xiaonan He, Xin Gao

With the widespread application of artificial intelligence (AI), particularly deep learning (DL) and vision-based large language models (VLLMs), in skin disease diagnosis, the need for interpretability becomes crucial. However, existing dermatology datasets are limited in their inclusion of concept-level meta-labels, and none offer rich medical descriptions in natural language. This deficiency impedes the advancement of LLM-based methods in dermatological diagnosis. To address this gap and provide a meticulously annotated dermatology dataset with comprehensive natural language descriptions, we introduce SkinCAP: a multi-modal dermatology dataset annotated with rich medical captions. SkinCAP comprises 4,000 images sourced from the Fitzpatrick 17k skin disease dataset and the Diverse Dermatology Images dataset, annotated by board-certified dermatologists to provide extensive medical descriptions and captions. Notably, SkinCAP represents the world's first such dataset and is publicly available at https://huggingface.co/datasets/joshuachou/SkinCAP.

Submitted: May 28, 2024