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IJCAI 2024Demo TrackDemo Track

GigaPevt: Multimodal Medical Assistant

Pavel Blinov, Konstantin Egorov, Ivan Sviridov, Nikolay Ivanov, Stepan Botman, Evgeniy Tagin, Stepan Kudin, Galina Zubkova, Andrey V. Savchenko

PDF 由论文原始站点提供,PaperCompass 不保存论文文件。DOI 10.24963/ijcai.2024/992 ↗

摘要

Building an intelligent and efficient medical assistant is still a challenging AI problem. The major limitation comes from the data modality scarceness, which reduces comprehensive patient perception. This demo paper presents GigaPevt, the first multimodal medical assistant that combines the dialog capabilities of large language models with specialized medical models. Such an approach shows immediate advantages in dialog quality and metric performance, with a 1.18% accuracy improvement in the question-answering task.