UMass-BioNLP at MEDIQA-M3G 2024: DermPrompt -- A Systematic Exploration of Prompt Engineering with GPT-4V for Dermatological Diagnosis

arXiv:2404.17749v2 Announce Type: replace-cross
Abstract: This paper presents our team's participation in the MEDIQA-ClinicalNLP2024 shared task B. We present a novel approach to diagnosing clinical dermatology cases by integrating large multimodal models, specifically leveraging the capabilities of GPT-4V under a retriever and a re-ranker framework. Our investigation reveals that GPT-4V, when used as a retrieval agent, can accurately retrieve the correct skin condition 85% of the time using dermatological images and brief patient histories. Additionally, we empirically show that Naive …

abstract arxiv capabilities cases clinical cs.ai cs.cl dermatology diagnosis engineering exploration gpt gpt-4v large multimodal models multimodal multimodal models novel paper prompt retriever team type