14 citations · 28 across the 9 of their papers we have counts for
9 papers
Compressor-Based Classification for Atrial Fibrillation Detection
Nikita Markov, Konstantin Ushenin, Yakov Bozhko +1
Atrial fibrillation (AF) is one of the most common arrhythmias with challenging public health implications. Therefore, automatic detection of AF episodes on ECG is one of the essen…
Computational anatomy atlas using multilayer perceptron with Lipschitz regularization
Konstantin Ushenin, Maksim Dzhigil, Vladislav Dordiuk
A computational anatomy atlas is a set of internal organ geometries. It is based on data of real patients and complemented with virtual cases by using a some numerical approach. At…
Statistical model for describing heart rate variability in normal rhythm and atrial fibrillation
Nikita Markov, Ilya Kotov, Konstantin Ushenin +1
Heart rate variability (HRV) indices describe properties of interbeat intervals in electrocardiogram (ECG). Usually HRV is measured exclusively in normal sinus rhythm (NSR) excludi…
Natural language processing for clusterization of genes according to their functions
Vladislav Dordiuk, Ekaterina Demicheva, Fernando Polanco Espino +1
There are hundreds of methods for analysis of data obtained in mRNA-sequencing. The most of them are focused on small number of genes. In this study, we propose an approach that re…
On uniqueness theorems for the inverse problem of Electrocardiography in the Sobolev spaces
Vitaly Kalinin, Alexander Shlapunov, Konstantin Ushenin
We consider a mathematical model related to reconstruction of cardiac electrical activity from ECG measurements on the body surface. An application of recent developments in solvin…
Anomaly Detection in Image Datasets Using Convolutional Neural Networks, Center Loss, and Mahalanobis Distance
Garnik Vareldzhan, Kirill Yurkov, Konstantin Ushenin
User activities generate a significant number of poor-quality or irrelevant images and data vectors that cannot be processed in the main data processing pipeline or included in the…
Effects of lead position, cardiac rhythm variation and drug-induced QT prolongation on performance of machine learning methods for ECG processing
Marat Bogdanov, Salim Baigildin, Aygul Fabarisova +2
Machine learning shows great performance in various problems of electrocardiography (ECG) signal analysis. However, collecting a dataset for biomedical engineering is a very diffic…
Phase mapping for cardiac unipolar electrograms with neural network instead of phase transformation
Konstantin Ushenin, Tatyana Nesterova, Dmitry Shmarko +1
A phase mapping is an approach to processing signals of electrograms recorded from the surface of cardiac tissue. The main concept of phase mapping is the application of the phase…
Comparison of UNet, ENet, and BoxENet for Segmentation of Mast Cells in Scans of Histological Slices
Alexander Karimov, Artem Razumov, Ruslana Manbatchurina +5
Deep neural networks show high accuracy in theproblem of semantic and instance segmentation of biomedicaldata. However, this approach is computationally expensive. Thecomputational…