# GigaPevt: Multimodal Medical Assistant

Source: [GigaPevt: Multimodal Medical Assistant](<https://www.sota2.com/research/paper/68fa74511e209131cea61090>)

Collection index: [llms.txt](<https://www.sota2.com/research/llms.txt>)

Data updated: 2025-10-26T03:07:41.757Z

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

Published: 2024-02-26T15:26:56.000Z

## Abstract

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 the 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.

## Recorded benchmark results

A research result applies to its stated dataset, split, metric and evaluation configuration. Compare like-for-like settings, preserve the metric's unit and direction, and distinguish paper-reported results from independent reproduction. The best result recorded here is not a claim of exhaustive, current global coverage.

## Original sources and implementation

[Original paper](<https://arxiv.org/abs/2402.16654>)

[PDF](<https://arxiv.org/pdf/2402.16654.pdf>)