91 citations · 116 across the 9 of their papers we have counts for
9 papers
Deciphering Diagnoses: How Large Language Models Explanations Influence Clinical Decision Making
D. Umerenkov, G. Zubkova, A. Nesterov
Clinical Decision Support Systems (CDSS) utilize evidence-based knowledge and patient data to offer real-time recommendations, with Large Language Models (LLMs) emerging as a promi…
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…
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…
RuBioRoBERTa: a pre-trained biomedical language model for Russian language biomedical text mining
Alexander Yalunin, Alexander Nesterov, Dmitriy Umerenkov
This paper presents several BERT-based models for Russian language biomedical text mining (RuBioBERT, RuBioRoBERTa). The models are pre-trained on a corpus of freely available text…
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…
Distantly supervised end-to-end medical entity extraction from electronic health records with human-level quality
Alexander Nesterov, Dmitry Umerenkov
Medical entity extraction (EE) is a standard procedure used as a first stage in medical texts processing. Usually Medical EE is a two-step process: named entity recognition (NER) 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…
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…
E.T.-RNN: Applying Deep Learning to Credit Loan Applications
Dmitrii Babaev, Maxim Savchenko, Alexander Tuzhilin +1
In this paper we present a novel approach to credit scoring of retail customers in the banking industry based on deep learning methods. We used RNNs on fine grained transnational d…