22 citations · 23 across the 4 of their papers we have counts for
5 papers
Towards Computationally Feasible Deep Active Learning
Akim Tsvigun, Artem Shelmanov, Gleb Kuzmin +5
Active learning (AL) is a prominent technique for reducing the annotation effort required for training machine learning models. Deep learning offers a solution for several essentia…
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…
Noise-Resilient Automatic Interpretation of Holter ECG Recordings
Konstantin Egorov, Elena Sokolova, Manvel Avetisian +1
Holter monitoring, a long-term ECG recording (24-hours and more), contains a large amount of valuable diagnostic information about the patient. Its interpretation becomes a difficu…
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…