Zobrazeno 1 - 9
of 9
pro vyhledávání: '"Manvel Avetisian"'
Autor:
Maria Sindeeva, Nikolay Chekanov, Manvel Avetisian, Tatiana I Shashkova, Nikita Baranov, Elian Malkin, Alexander Lapin, Olga Kardymon, Veniamin Fishman
Publikováno v:
GigaScience. 12
Interpretation of noncoding genomic variants is one of the most important challenges in human genetics. Machine learning methods have emerged recently as a powerful tool to solve this problem. State-of-the-art approaches allow prediction of transcrip
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::aa82e17c3433f8abc54ba1faa94d2e48
https://doi.org/10.1093/gigascience/giad015
https://doi.org/10.1093/gigascience/giad015
Autor:
Alexandr Nesterov, Galina Zubkova, Zulfat Miftahutdinov, Vladimir Kokh, Elena Tutubalina, Artem Shelmanov, Anton Alekseev, Manvel Avetisian, Andrey Chertok, Sergey Nikolenko
Publikováno v:
Findings of the Association for Computational Linguistics: ACL 2022.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::7848bb018c1e50032ef9cc464103c96e
https://doi.org/10.18653/v1/2022.findings-acl.21
https://doi.org/10.18653/v1/2022.findings-acl.21
Autor:
Maria Sindeeva, Nikolay Chekanov, Manvel Avetisian, Nikita Baranov, Elian Malkin, Alexander Lapin, Olga Kardymon, Veniamin Fishman
Interpretation of non-coding genomic variants is one of the most important challenges in human genetics. Machine learning methods have emerged recently as a powerful tool to solve this problem. State-of-the-art approaches allow prediction of transcri
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::7ff867ff84b97b896a542b979f193842
https://doi.org/10.1101/2021.12.31.474623
https://doi.org/10.1101/2021.12.31.474623
Autor:
Artem Vazhentsev, Gleb Kuzmin, Artem Shelmanov, Akim Tsvigun, Evgenii Tsymbalov, Kirill Fedyanin, Maxim Panov, Alexander Panchenko, Gleb Gusev, Mikhail Burtsev, Manvel Avetisian, Leonid Zhukov
Publikováno v:
Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::8e0233161569458c8d06460043ecef82
https://doi.org/10.18653/v1/2022.acl-long.566
https://doi.org/10.18653/v1/2022.acl-long.566
Autor:
Alexander Ponomarchuk, Ilya Burenko, Elian Malkin, Ivan Nazarov, Vladimir Kokh, Manvel Avetisian, Leonid Zhukov
The COVID-19 pandemic created significant interest and demand for infection detection and monitoring solutions. In this paper, we propose a machine learning method to quickly detect COVID-19 using audio recordings made on consumer devices. The approa
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::fe9329fd9e0c1d62ab50abf5ce0f5119
Autor:
Ilya Burenko, Alexander Tuzhilin, Vladimir Kokh, Manvel Avetisian, Aleksandr Nikolaev, Elena Sokolova, Konstantin Egorov, Dmitry Umerenkov, Alexander Ponomarchuk, Aleksandr Nesterov
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 essential for formulating treatment recommendations and prioritizing
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::5c8c320478581b0aa5180f1e58daecad
Publikováno v:
BIOSIGNALS
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 difficult and time-consuming task for the doctor who analyzes them because ev
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::49b57ff6b60036a18d76a8796b9289f9
http://arxiv.org/abs/2011.09303
http://arxiv.org/abs/2011.09303
Publikováno v:
Lecture Notes in Computer Science ISBN: 9783030322472
MICCAI (3)
MICCAI (3)
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 architecture for the stroke identification problem using non-contrast
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::9eca6752827a1986f5ac7244eba5fc1f
https://doi.org/10.1007/978-3-030-32248-9_91
https://doi.org/10.1007/978-3-030-32248-9_91
Publikováno v:
BASE-Bielefeld Academic Search Engine
Artificial Intelligence in Medicine ISBN: 9783030591366
AIME
Artificial Intelligence in Medicine ISBN: 9783030591366
AIME
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 and present comprehensive historical review of the problem and proposed
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a86b0ceb8edee8d919b3ee0cc81de8c2