Speaker
Description
The landscape of computational bioimaging is rapidly evolving, featuring a vast array of tools, workflows, and documentation. This growth underscores the need for more accessible analytical tools to deliver comprehensive capabilities to the scientific community. The BioImage.IO Chatbot, developed in response to this need, leverages Large Language Models (LLMs) and Retrieval Augmented Generation (RAG) techniques between others to offer an interactive and intuitive platform for engaging with advanced bioimage analysis resources. This innovative tool not only retrieves information and executes pre-existing models but also enables users to create custom extensions tailored to their specific research needs, such as automating microscopy operations or crafting specialized analysis workflows. A primary objective of the BioImage.IO Chatbot is to lower the barriers to entry for researchers, fostering a more collaborative and enriched scientific community. Designed to be community-driven, the chatbot continually evolves, integrating various tools, workflows, and knowledge contributed by users. We actively encourage community contributions to expand the chatbot’s capabilities, ensuring it remains at the cutting edge of bioimage analysis technology. All in all, the BioImage.IO Chatbot is not just changing the landscape of bioimage analysis but revolutionizing it.
| Authors | Wanlu Lei, Caterina Fuster-Barceló*, Gabriel Reder, Arrate Muñoz-Barrutia, Wei Ouyang |
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| Keywords | bioimage analysis, large language models, chatbot, retrieval augmented generation, microscopy images |
