49 citations · 90 across the 8 of their papers we have counts for
8 papers
FREED++: Improving RL Agents for Fragment-Based Molecule Generation by Thorough Reproduction
Alexander Telepov, Artem Tsypin, Kuzma Khrabrov +8
A rational design of new therapeutic drugs aims to find a molecular structure with desired biological functionality, e.g., an ability to activate or suppress a specific protein via…
Gradual Optimization Learning for Conformational Energy Minimization
Artem Tsypin, Leonid Ugadiarov, Kuzma Khrabrov +7
Molecular conformation optimization is crucial to computer-aided drug discovery and materials design. Traditional energy minimization techniques rely on iterative optimization meth…
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…
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…
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…