49 citations · 117 across the 12 of their papers we have counts for
12 papers
HAMSA: Hijacking Aligned Compact Models via Stealthy Automation
Alexey Krylov, Iskander Vagizov, Dmitrii Korzh +6
Large Language Models (LLMs), especially their compact efficiency-oriented variants, remain susceptible to jailbreak attacks that can elicit harmful outputs despite extensive align…
Can-SAVE: Deploying Low-Cost and Population-Scale Cancer Screening via Survival Analysis Variables and EHR
Petr Philonenko, Vladimir Kokh, Pavel Blinov
Conventional medical cancer screening methods are costly, labor-intensive, and extremely difficult to scale. Although AI can improve cancer detection, most systems rely on complex…
Predicting COVID-19 and pneumonia complications from admission texts
Dmitriy Umerenkov, Oleg Cherkashin, Alexander Nesterov +4
In this paper we present a novel approach to risk assessment for patients hospitalized with pneumonia or COVID-19 based on their admission reports. We applied a Longformer neural n…
Whole-body PET image denoising for reduced acquisition time
Ivan Kruzhilov, Stepan Kudin, Luka Vetoshkin +2
This paper evaluates the performance of supervised and unsupervised deep learning models for denoising positron emission tomography (PET) images in the presence of reduced acquisit…
NeuralSympCheck: A Symptom Checking and Disease Diagnostic Neural Model with Logic Regularization
Aleksandr Nesterov, Bulat Ibragimov, Dmitriy Umerenkov +3
The symptom checking systems inquire users for their symptoms and perform a rapid and affordable medical assessment of their condition. The basic symptom checking systems based on…
Abstractive summarization of hospitalisation histories with transformer networks
Alexander Yalunin, Dmitriy Umerenkov, Vladimir Kokh
In this paper we present a novel approach to abstractive summarization of patient hospitalisation histories. We applied an encoder-decoder framework with Longformer neural network…
RuMedBench: A Russian Medical Language Understanding Benchmark
Pavel Blinov, Arina Reshetnikova, Aleksandr Nesterov +2
The paper describes the open Russian medical language understanding benchmark covering several task types (classification, question answering, natural language inference, named ent…
Project Achoo: A Practical Model and Application for COVID-19 Detection from Recordings of Breath, Voice, and Cough
Alexander Ponomarchuk, Ilya Burenko, Elian Malkin +4
The COVID-19 pandemic created a significant interest and demand for infection detection and monitoring solutions. In this paper we propose a machine learning method to quickly tria…
Medical Profile Model: Scientific and Practical Applications in Healthcare
Pavel Blinov, Vladimir Kokh
The paper researches the problem of representation learning for electronic health records. We present the patient histories as temporal sequences of diseases for which embeddings a…
CoRSAI: A System for Robust Interpretation of CT Scans of COVID-19 Patients Using Deep Learning
Manvel Avetisian, Ilya Burenko, Konstantin Egorov +7
Analysis of chest CT scans can be used in detecting parts of lungs that are affected by infectious diseases such as COVID-19.Determining the volume of lungs affected by lesions is…
Predicting Clinical Diagnosis from Patients Electronic Health Records Using BERT-based Neural Networks
Pavel Blinov, Manvel Avetisian, Vladimir Kokh +2
In this paper we study the problem of predicting clinical diagnoses from textual Electronic Health Records (EHR) data. We show the importance of this problem in medical community a…
Radiologist-level stroke classification on non-contrast CT scans with Deep U-Net
Manvel Avetisian, Vladimir Kokh, Alex Tuzhilin +1
Segmentation of ischemic stroke and intracranial hemorrhage on computed tomography is essential for investigation and treatment of stroke. In this paper, we modified the U-Net CNN…