activity
20232025
most citedMedSyn: LLM-based Synthetic Medical Text Generation Framework

28 citations · 40 across the 6 of their papers we have counts for

collaborators

8 papers

cs.CV2025

Gaze into the Heart: A Multi-View Video Dataset for rPPG and Health Biomarkers Estimation

Konstantin Egorov, Stepan Botman, Pavel Blinov +4

Progress in remote PhotoPlethysmoGraphy (rPPG) is limited by the critical issues of existing publicly available datasets: small size, privacy concerns with facial videos, and lack…

cs.HC2025

3MDBench: Medical Multimodal Multi-agent Dialogue Benchmark

Ivan Sviridov, Amina Miftakhova, Artemiy Tereshchenko +3

Though Large Vision-Language Models (LVLMs) are being actively explored in medicine, their ability to conduct complex real-world telemedicine consultations combining accurate diagn…

cs.CL2025

RuCCoD: Towards Automated ICD Coding in Russian

Aleksandr Nesterov, Andrey Sakhovskiy, Ivan Sviridov +5

This study investigates the feasibility of automating clinical coding in Russian, a language with limited biomedical resources. We present a new dataset for ICD coding, which inclu…

cs.CL202428 cited

MedSyn: LLM-based Synthetic Medical Text Generation Framework

Gleb Kumichev, Pavel Blinov, Yulia Kuzkina +5

Generating synthetic text addresses the challenge of data availability in privacy-sensitive domains such as healthcare. This study explores the applicability of synthetic data in r…

cs.CV2024

CardioSyntax: end-to-end SYNTAX score prediction -- dataset, benchmark and method

Alexander Ponomarchuk, Ivan Kruzhilov, Galina Zubkova +4

The SYNTAX score has become a widely used measure of coronary disease severity, crucial in selecting the optimal mode of the revascularization procedure. This paper introduces a ne…

cs.AI2024

GigaPevt: Multimodal Medical Assistant

Pavel Blinov, Konstantin Egorov, Ivan Sviridov +6

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…