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Conventional task- and modality-specific artificial intelligence (AI) modelsare inflexible in real-world deployment and maintenance for biomedicine. At thesame time, the growing availability of biomedical data, coupled with theadvancements in modern multi-modal multi-task AI techniques, has paved the wayfor the emergence of generalist biomedical AI solutions. These solutions holdthe potential to interpret different medical modalities and produce expressiveoutputs such as free-text reports or disease diagnosis. Here, we proposeBiomedGPT, the first open-source and generalist visual language AI for diversebiomedical tasks. BiomedGPT achieved 16 state-of-the-art results across fiveclinically significant tasks on 26 datasets. Notably, it outperformed OpenAI'sGPT-4 with vision (GPT-4V) in radiology human evaluation and surpassed Google'sMed-PaLM M (12B) in breast cancer diagnosis and medical visual questionanswering. Moreover, BiomedGPT facilitates zero-shot transfer learning, greatlyenhancing its utility as a biomedical assistant, similar to ChatGPT. Our methoddemonstrates effective training with diverse datasets can lead to morepractical biomedical AI.

BiomedGPT: A Unified and Generalist Biomedical Generative Pre-trained Transformer for Vision, Language, and Multimodal Tasks