An international research team led by Assistant Professor Zhiyu Wan from ShanghaiTech University has recently published groundbreaking findings in the journal Health Data Science, highlighting biases in multimodal large language models (LLMs) such as ChatGPT-4 and LLaVA in diagnosing skin diseases from medical images. The study systematically evaluated these AI models across different sex and age groups.
Utilizing approximately 10,000 dermatoscopic images, the study focused on three common skin diseases: melanoma, melanocytic nevi, and benign keratosis-like lesions. Results revealed that while ChatGPT-4 and LLaVA outperformed most traditional deep learning models overall, ChatGPT-4 showed greater fairness across demographic groups,…
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