Pre-trained multimodal large language model enhances dermatological diagnosis using SkinGPT-4.
Nat Commun
; 15(1): 5649, 2024 Jul 05.
Article
em En
| MEDLINE
| ID: mdl-38969632
ABSTRACT
Large language models (LLMs) are seen to have tremendous potential in advancing medical diagnosis recently, particularly in dermatological diagnosis, which is a very important task as skin and subcutaneous diseases rank high among the leading contributors to the global burden of nonfatal diseases. Here we present SkinGPT-4, which is an interactive dermatology diagnostic system based on multimodal large language models. We have aligned a pre-trained vision transformer with an LLM named Llama-2-13b-chat by collecting an extensive collection of skin disease images (comprising 52,929 publicly available and proprietary images) along with clinical concepts and doctors' notes, and designing a two-step training strategy. We have quantitatively evaluated SkinGPT-4 on 150 real-life cases with board-certified dermatologists. With SkinGPT-4, users could upload their own skin photos for diagnosis, and the system could autonomously evaluate the images, identify the characteristics and categories of the skin conditions, perform in-depth analysis, and provide interactive treatment recommendations.
Texto completo:
1
Base de dados:
MEDLINE
Assunto principal:
Dermatopatias
/
Dermatologia
Limite:
Humans
Idioma:
En
Ano de publicação:
2024
Tipo de documento:
Article