A. Sboev

发表

Data-driven model for identifying related pharmaceutically-significant entities in clinical texts

A. Sboev, Gleb Rylkov, R. Rybka, 2022, INTERNATIONAL CONFERENCE OF NUMERICAL ANALYSIS AND APPLIED MATHEMATICS ICNAAM 2020.

Extraction of the Relations among Significant Pharmacological Entities in Russian-Language Reviews of Internet Users on Medications

A. Sboev, Gleb Rylkov, R. Rybka, 2022, Big Data Cogn. Comput..

Evaluation of Machine Learning Methods for Relation Extraction Between Drug Adverse Effects and Medications in Russian Texts of Internet User Reviews

A. Sboev, Gleb Rylkov, R. Rybka, 2021, Proceedings of The 5th International Workshop on Deep Learning in Computational Physics — PoS(DLCP2021).

Coronary heart disease diagnosis by artificial neural networks including genetic polymorphisms and clinical parameters.

A. Sboev, O. Atkov, S. Gorokhova, 2012, Journal of cardiology.

Solving a classification task by spiking neural network with STDP based on rate and temporal input encoding

A. Sboev, R. Rybka, A. Serenko, 2020, Mathematical Methods in the Applied Sciences.

Neural-network Method for Determining Text Author’s Sentiment to an Aspect Specified by the Named Entity

A. Sboev, R. Rybka, A. Gryaznov, 2020 .

A probabilistically entropic mechanism of topical clusterisation along with thematic annotation for evolution analysis of meaningful social information of internet sources

D. V. Gydovskikh, A. Sboev, R. Rybka, 2017 .

Strict baselines for Covid-19 forecasting and ML perspective for USA and Russia

A. Sboev, R. Rybka, I. Moloshnikov, 2022, 2207.07689.

A spiking neural network with fixed synaptic weights based on logistic maps for a classification task

A. Sboev, R. Rybka, A. Serenko, 2022, Proceedings of The 6th International Workshop on Deep Learning in Computational Physics — PoS(DLCP2022).

Relation Extraction from Texts Containing Pharmacologically Significant Information on base of Multilingual Language Models

A. Sboev, R. Rybka, A. Gryaznov, 2022, Proceedings of The 6th International Workshop on Deep Learning in Computational Physics — PoS(DLCP2022).

Accuracy of COVID-19 evolution models for different forecast horizons

A. Sboev, R. Rybka, I. Moloshnikov, 2022, Proceedings of The 6th International Workshop on Deep Learning in Computational Physics — PoS(DLCP2022).

Morpho-syntactic parsing based on neural networks and corpus data

Roman Rybka, Ivan Moloshnikov, Dmitry Gudovskikh, 2015, 2015 Artificial Intelligence and Natural Language and Information Extraction, Social Media and Web Search FRUCT Conference (AINL-ISMW FRUCT).

Adverse Drug Reaction Concept Normalization in Russian-Language Reviews of Internet Users

A. Sboev, Gleb Rylkov, R. Rybka, 2022, Big Data Cogn. Comput..

Analysis of the Full-Size Russian Corpus of Internet Drug Reviews with Complex NER Labeling Using Deep Learning Neural Networks and Language Models

A. Sboev, Gleb Rylkov, R. Rybka, 2022, Applied Sciences.

A comparison of learning abilities of spiking networks with different spike timing-dependent plasticity forms

Alexander Sboev, Roman Rybka, Alexey Serenko, 2016 .

Automatic gender identification of author of Russian text by machine learning and neural net algorithms in case of gender deception

Alexander Sboev, Roman Rybka, Ivan Moloshnikov, 2017, BICA.

Solving a classification task by spiking neurons with STDP and temporal coding

Alexander Sboev, Roman Rybka, Alexey Serenko, 2017, BICA.

Automated system for preventing accidents during well construction

A. Sboev, N. Eremin, M. Gelfgat, 2021 .

On increasing the productive time of drilling oil and gas wells using machine learning methods

A. Sboev, A. Gryaznov, I. Moloshnikov, 2020 .

Application of artificial intelligence methods for identifying and predicting complications in the construction of oil and gas wells: problems and solutions

Alexander Sboev, Alexander D. Chernikov, Nikolay A. Eremin, 2020 .

Human Brain Structural Organization in Healthy Volunteers and Patients with Schizophrenia

B. Velichkovsky, V. Ushakov, S. Kartashov, 2017, BICA 2017.

Ensembling SNNs with STDP Learning on Base of Rate Stabilization for Image Classification

Alexander Sboev, Alexey Serenko, Danila Vlasov, 2020 .

An analysis of full-size Russian complexly NER labelled corpus of Internet user reviews on the drugs based on deep learning and language neural nets pdf

Alexander Sboev, Roman Rybka, Ivan Moloshnikov, 2021, ArXiv.

The complex of neural networks and probabilistic methods for mathematical modeling of the syntactic structure of a sentence of natural language

Roman Rybka, Ivan Moloshnikov, Dmitry Gudovskikh, 2016 .

Spiking neural network reinforcement learning method based on temporal coding and STDP

Alexander Sboev, Roman Rybka, Alexey Serenko, 2018, BICA.

The Russian Language Corpus and a Neural Network to Analyse Internet Tweet Reports About Covid-19

A. Sboev, R. Rybka, I. Moloshnikov, 2021, Proceedings of The 5th International Workshop on Deep Learning in Computational Physics — PoS(DLCP2021).

A probabilistic-entropy approach of finding thematically similar documents with creating context-semantic graph for investigating evolution of society opinion

Roman Rybka, Ivan Moloshnikov, A. G. Sboev, 2016 .

Visualization of Subtopics of the Thematic Document Collection Using the Context-Semantic Graph

Roman Rybka, Ivan Moloshnikov, Dmitry Gudovskikh, 2015, 2015 International Conference on Computational Science and Computational Intelligence (CSCI).

An Algorithm of Finding Thematically Similar Documents with Creating Context-semantic Graph Based on Probabilistic-entropy Approach

Roman Rybka, Ivan Moloshnikov, A. G. Sboev, 2015 .

Coronary heart disease diagnosis by artificial neural networks including genetic polymorphisms and clinical parameters.

A. Sboev, O. Atkov, S. Gorokhova, 2012, Journal of cardiology.

Solving a classification task with temporal input encoding by a spiking neural network with memristor-type plasticity in the form of hyperbolic tangent

A. Sboev, R. Rybka, A. Serenko, 2023, AIP Conference Proceedings.

Syntactic Analysis of the Sentences of the Russian Language Based on Neural Networks

Alexander Sboev, Roman Rybka, Ivan Moloshnikov, 2015 .

GEEF: A neural network model for automatic essay feedback generation by integrating writing skills assessment

A. Sboev, Ilya Makarov, Yuanchao Liu, 2023, Expert Syst. Appl..