Malignancies

Assessing the Utility of Multimodal Large Language Models (GPT-4 Vision and Large Language and Vision Assistant) in Identifying Melanoma Across Different Skin Tones

“…Our data set comprised macroscopic images (900 × 1100 pixels; 96-dpi resolution) of melanomas (malignant) and melanocytic nevi (benign) obtained from the publicly available and validated MClass-D data set [ 6 ], Dermnet NZ [ 7 ], and dermatology textbooks [ 8 ]. Each LLM was provided with 20 unique text-based prompts that were each tested on 3 images (n=60 unique image-prompt combinations) consisting of questions about “moles” (the term used for benign and malignant lesions), instructions, and image-based prompts where the image was annotated to alter the focus.…”