BiomedGPT: A Unified and Generalist Biomedical Generative Pre-trained Transformer for Vision, Language, and Multimodal Tasks
CoRR(2023)
摘要
Conventional task- and modality-specific artificial intelligence (AI) models
are inflexible in real-world deployment and maintenance for biomedicine. At the
same time, the growing availability of biomedical data, coupled with the
advancements in modern multi-modal multi-task AI techniques, has paved the way
for the emergence of generalist biomedical AI solutions. These solutions hold
the potential to interpret different medical modalities and produce expressive
outputs such as free-text reports or disease diagnosis. Here, we propose
BiomedGPT, the first open-source and generalist visual language AI for diverse
biomedical tasks. BiomedGPT achieved 16 state-of-the-art results across five
clinically significant tasks on 26 datasets. Notably, it outperformed OpenAI's
GPT-4 with vision (GPT-4V) in radiology human evaluation and surpassed Google's
Med-PaLM M (12B) in breast cancer diagnosis and medical visual question
answering. Moreover, BiomedGPT facilitates zero-shot transfer learning, greatly
enhancing its utility as a biomedical assistant, similar to ChatGPT. Our method
demonstrates effective training with diverse datasets can lead to more
practical biomedical AI.
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关键词
multimodal tasks,transformer,vision,unified,pre-trained
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