Этическое обеспечение исследований с участием людей для разработчиков роботов, приборов и технологий
Selected topics in reinforcement learning: practical hands-on
Moiseev I., Balabaeva K., Kovalchuk S. Open and Extensible Benchmark for Explainable Artificial Intelligence Methods. Algorithms. 2025. Vol. 18. No. 2. pp. 85.. doi: 10.3390/a18020085
Pimenov A., Kovalchuk S. Evaluation and Prediction of Human Software Developers’ Perception of Large Language Models Suggestions Using GitHub Data. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 2025. Vol. 15406. pp. 347-361.. doi: 10.1007/978-3-031-78459-0_25
Fedrushkov D., Tereshchenko D., Kovalchuk S., Aliev A. Improving project-level code generation using combined relevant context. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 2025. Vol. 15906. pp. 438-445.. doi: 10.1007/978-3-031-97635-3_52
Li C., Petruchik O., Grishanina E., Kovalchuk S. Multi-agent norm perception and induction in distributed healthcare. Journal of Biomedical Informatics. 2025. Vol. 166. pp. 104835.. doi: 10.1016/j.jbi.2025.104835
Гофман О.О., Кузьмин А.Ю., Ковальчук С.В. Симбиотическое взаимодействие «человек — искусственный интеллект» в системах поддержки принятия решений [Symbiotic human-artificial intelligence interaction in decision support systems]. Организационная психология [Organizatsionnaya psikologiya]. 2025. Т. 15. № 1. С. 297–321.. doi: 10.17323/2312-5942-2025-15-1-297-321
Fu X., Krzhizhanovskaya V., Yakovlev A., Kovalchuk S. Modelling Diversity in Hospital Strategies in City-Scale Ambulance Dispatching with Coupled Game-Theoretic Model and Discrete-Event Simulation. Journal of Biomedical Informatics. 2025. Vol. 162. pp. 104777.. doi: 10.1016/j.jbi.2025.104777
Ireddy A.T., Kovalchuk S.V. Simulation Modeling of Clinical Decision Making for Personalized Policy Identification. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 2025. Vol. 15906. pp. 412-420.. doi: 10.1007/978-3-031-97635-3_49
Li C., Zhang D., Ren F., Kovalchuk S. Cross-Scale Modeling of Healthcare Norms and Patient Features Dynamics with Interpretable Machine Learning. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 2025. Vol. 15908. pp. 113–127.. doi: 10.1007/978-3-031-97557-8_9
Towards Modeling of Distributed Intelligence Systems in Modern Healthcare.Сборник тезисов докладов конгресса молодых ученых (XIII Всероссийский конгресс молодых ученых, 8-11апреля 2024г.) [электронное издание]
Моделирование индивидуальных когнитивных состояний оператора в рамках взаимодействия человек-искусственный интеллект при работе с системами поддержки принятия решений в сложных предметных областях
Ireddy A.T., Kovalchuk S.V. Modelling Information Perceiving within Clinical Decision Support using Inverse Reinforcement Learning. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 2024. Vol. 14835. pp. 210–223.. doi: 10.1007/978-3-031-63772-8_20
Fedrushkov D., Kovalchuk S., Lomshakov V., Aliev A. Beam Search for Improvement of Code Generation in Answering Programming Questions with Code. Communications in Computer and Information Science. 2024. Vol. 2241. pp. 194-208.. doi: 10.1007/978-3-031-73372-7_14
Ковальчук С.В., Иредди А. Моделирование индивидуальных когнитивных состояний оператора в рамках взаимодействия человек-искусственный интеллект при работе с системами поддержки принятия решений в сложных предметных областях. X Международная конференция по когнитивной науке (Пятигорск, 26-30 июня 2024 г.) [тезисы докладов]. 2024. Т. Часть 1. С. 144-146.
Pogrebnoi D., Funkner A., Kovalchuk S. RuMedSpellchecker: A new approach for advanced spelling error correction in Russian electronic health records. Journal of Computational Science. 2024. Vol. 82. pp. 102393.. doi: 10.1016/j.jocs.2024.102393
Кубряк О.В., Ковальчук С.В. Искусственный сенсорный компонент в системе человек - машина с комбинированной обратной связью. Проблемы управления. 2024. № 6. С. 27-37.
Kovalchuk S.V., Li C., Kubryak O.V. Towards Explaining Emergent Behavior in Multi-Agent Systems Micro-Parameter Space Structuring with Feature Importance in Heatbug Model. 2024 IEEE/WIC International Conference on Web Intelligence and Intelligent Agent Technology (WI-IAT). 2024. pp. 824-829.. doi: 10.1109/WI-IAT62293.2024.00134
Gorbatovski A., Kovalchuk S. Reinforcement Learning for Question Answering in Programming domain using Public Community Scoring as a Human Feedback. AAMAS '24: Proceedings of the 23rd International Conference on Autonomous Agents and Multiagent Systems. 2024. pp. 2294–2296.
Kovalchuk S.V., Ireddy A.T. Prediction of Users Perceptional State for Human-Centric Decision Support Systems in Complex Domains through Implicit Cognitive State Modeling. Proceedings of the Annual Meeting of the Cognitive Science Society. 2024. Vol. 46. pp. 3257-3264.
Солдатов А.Н., Солдатов И.К., Ковальчук С.В. Моделирование восприятия рекомендаций системы поддержки принятия врачебных решений на основе предсказательного моделирования при проведении профилактических осмотров врачами-стоматологами [Modeling perceiving of recommendations provided by clinical decision support system based on predictive modeling within dental preventive screening]. Научно-технический вестник информационных технологий, механики и оптики [Scientific and Technical Journal of Information Technologies, Mechanics and Optics]. 2024. Т. 24. № 2. С. 335-338.. doi: 10.17586/2226-1494-2024-24-2-335-338
Li C., Petruchik O., Grishanina E., Kovalchuk S. Modelling of practice sharing in complex distributed healthcare system. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 2024. Vol. 14835. pp. 224-238.. doi: 10.1007/978-3-031-63772-8_21
Ireddy A.T., Kovalchuk S.V., Beloglazov L.A., Zatsepina E.А., Ионов М.В. Evaluating Perceived Complexity of Process Models from a Targeted Survey of Healthcare Domain Specialists. International Conference on Mathematical Modeling and Supercomputer Technologies. 2024. pp. in press.
Gorbatovski A.V., Razin A.D., Aliev A.A., Kovalchuk S.V. Improving question answering in programming domain with pretrained language model finetuning using structured diverse online forum data. Научно-технический вестник информационных технологий, механики и оптики [Scientific and Technical Journal of Information Technologies, Mechanics and Optics]. 2024. Vol. 24. No. 6. pp. 1024-1034.. doi: 10.17586/2226-1494-2024-24-6-1024-1034
Kovalchuk S., Fedrushkov D., Lomshakov V., Aliev A. Test-based and metric-based evaluation of code generation models for practical question answering. 2023 International Conference on Code Quality (ICCQ). 2023. pp. 73-86.. doi: 10.1109/ICCQ57276.2023.10114665
Elkhovskaya L.O., Kshenin A.D., Balakhontceva M.A., Ionov M.V., Kovalchuk S.V. Extending Process Discovery with Model Complexity Optimization and Cyclic States Identification: Application to Healthcare Processes. Algorithms. 2023. Vol. 16. No. 1. pp. 57.. doi: 10.3390/a16010057
Pogrebnoi D., Funkner A., Kovalchuk S. RuMedSpellchecker: Correcting Spelling Errors for Natural Russian Language in Electronic Health Records Using Machine Learning Techniques. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 2023. Vol. 10475. pp. 213-227.. doi: 10.1007/978-3-031-36024-4_16
Улучшение генеративных систем ответов на вопросы сообщества, в области программирования, основанные на обратной связи людей
Рванова Л. (науч. рук. Ковальчук С.В.) Automatic Question Answering Using Topic Modeling in Programming Domain
Kabyshev M.V., Kovalchuk S.V. Analysis and control of user engagement in personalized mobile assisting software for chronic disease patients. Научно-технический вестник информационных технологий, механики и оптики [Scientific and Technical Journal of Information Technologies, Mechanics and Optics]. 2023. Vol. 23. No. 2(144). pp. 331-339.. doi: 10.17586/2226-1494-2023-23-2-331-339
Gorbatovski A., Kovalchuk S. Bayesian Networks for Named Entity Prediction in Programming Community Question Answering. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 2023. Vol. 14074. pp. 282–289.. doi: 10.1007/978-3-031-36021-3_28
Abuhay T., Robinson S., Mamuye A., Kovalchuk S.V. Machine learning integrated patient flow simulation: why and how?. Journal of Simulation. 2023. Vol. 17. No. 5. pp. 580-593.. doi: 10.1080/17477778.2023.2217334
Kopanitsa G., Metsker O., Kovalchuk S. Machine Learning Methods for Pregnancy and Childbirth Risk Management. Journal of Personalized Medicine. 2023. Vol. 13. No. 6. pp. 975.. doi: 10.3390/jpm13060975
Ireddy A.T., Kovalchuk S.V. An Experimental Outlook on Quality Metrics for Process Modelling: A Systematic Review and Meta Analysis. Algorithms. 2023. Vol. 16. No. 6. pp. 295.. doi: 10.3390/a16060295
Kubryak O., Kovalchuk S.V., Bagdasaryan N.G. Assessment of Cognitive Behavioral Characteristics in Intelligent Systems with Predictive Ability and Computing Power. Philosophies. 2023. Vol. 8. No. 5. pp. 75.. doi: 10.3390/philosophies8050075
Rvanova L., Kovalchuk S. Automatic Structuring of Topics for Natural Language Generation in Community Question Answering in Programming Domain. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 2023. Vol. 14074. pp. 322–329.. doi: 10.1007/978-3-031-36021-3_33
Rvanova L., Kovalchuk S.V. Using regular expressions for thematic classification in the task of question answering. Сборник трудов XII Конгресса молодых ученых (Санкт-Петербург, 3-6 апреля 2023 г.). 2023. Vol. 4. No. 1. pp. 57-59.
Babikov I., Kovalchuk S., Soldatov I. Semi-supervised method for improving general-purpose and domain-specific textual corpora labels. Procedia Computer Science. 2023. Vol. 229. pp. 168-176.. doi: 10.1016/j.procs.2023.12.018
Isakov T., Kovalchuk S. Methodology of event extraction from unstructured medical texts on the example of the Russian language. Procedia Computer Science. 2023. Vol. 229. pp. 101-108.. doi: 10.1016/j.procs.2023.12.011
Zhdanova E., Korneev I., Kovalchuk S. Predictive modeling of multistep clinical pathways: application to infertility treatment process. Procedia Computer Science. 2023. Vol. 229. pp. 272-283.. doi: 10.1016/j.procs.2023.12.029
Study of the user behaviour caused by automatic symptom checkers call to action
COVID-19 Treatment Process Identification: A Case Study in Russian Hospital for Cardiology
Rezvykh A.D., Ovcharenko A., Lemeshkin R.N., Kovalchuk S.V. . Modeling the workflow of a field hospital in earthquake conditions. Procedia Computer Science. 2022. Vol. 212. pp. 330-339.. doi: 10.1016/j.procs.2022.11.017
Babikov I., Kovalchuk S., Soldatov I., Grebnev G. Structuring Research Directions in Medical Domain with Topic Modeling: Application for PhD Theses Synopses in Dentistry. Studies in health technology and informatics. 2022. Vol. 299. pp. 229-234.. doi: 10.3233/SHTI220989
Derevitskii I., Mramorov N.D., Usoltsev S., Kovalchuk S.V. Hybrid Bayesian Network-Based Modeling: COVID-19-Pneumonia Case. Journal of Personalized Medicine. 2022. Vol. 12. No. 8. pp. 1325.. doi: 10.3390/jpm12081325
Detkov N., Balabaeva K., Kovalchuk S.V. Exploring the Relationship Between Error and Interpretation of the Segmentation Model's Prediction. Procedia Computer Science. 2022. Vol. 212. pp. 122-131.. doi: 10.1016/j.procs.2022.10.214
Kopanitsa G., Kovalchuk S. Study of the User Behaviour Caused by Automatic Recommendation Systems Call to Action. Studies in health technology and informatics. 2022. Vol. 299. pp. 89-96.. doi: 10.3233/SHTI220966
Ионов М.В., Болгова Е.В., Звартау Н.Э., Авдонина Н.Г., Балахонцева М.А., Ковальчук С.В., Конради А.О. Внедрение системы поддержки принятия решений для повышения качества медицинских данных пациентов с артериальной гипертензией [Implementation of a clinical decision support system to improve the medical data quality for hypertensive patients]. Научно-технический вестник информационных технологий, механики и оптики [Scientific and Technical Journal of Information Technologies, Mechanics and Optics]. 2022. Т. 22. № 1(137). С. 217-222.. doi: 10.17586/2226-1494-2022-22-1-217-222
Koshman V., Funkner A., Kovalchuk S. An Unsupervised Approach to Structuring and Analyzing Repetitive Semantic Structures in Free Text of Electronic Medical Records. Journal of Personalized Medicine. 2022. Vol. 12. No. 1. pp. 25.. doi: 10.3390/jpm12010025
Pavlovskii V., Derevitskii I., Kovalchuk S.V. Hybrid genetic predictive modeling for finding optimal multipurpose multicomponent therapy. Journal of Computational Science. 2022. Vol. 63. pp. 101772.. doi: 10.1016/j.jocs.2022.101772
Balabaeva K., Kovalchuk S. Neural Additive Models for Explainable Heart Attack Prediction. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 2022. Vol. 13352. pp. 113-121.. doi: 10.1007/978-3-031-08757-8_11
Kovalchuk S.V., Krzhizhanovskaya V.V., Paszynski M., Kranzlmuller D., Dongarra J., Sloot P. Computational science for a better future. Journal of Computational Science. 2022. Vol. 62. pp. 101745.. doi: 10.1016/j.jocs.2022.101745
Kovalchuk S.V., Kopanitsa G.D., Derevitskii I., Matveev G.A., Savitskaya D.A. Three-stage intelligent support of clinical decision making for higher trust, validity, and explainability. Journal of Biomedical Informatics. 2022. Vol. 127. pp. 104013.. doi: 10.1016/j.jbi.2022.104013
Funkner A.A., Yakovlev A., Kovalchuk S. Surrogate-assisted performance prediction for data-driven knowledge discovery algorithms: Application to evolutionary modeling of clinical pathways. Journal of Computational Science. 2022. Vol. 59. pp. 101562.. doi: 10.1016/j.jocs.2022.101562
Milykh S., Kovalchuk S. Treatment trajectories graph compression algorithm based on cliques. Studies in health technology and informatics. 2021. Vol. 285. pp. 300-305.. doi: 10.3233/SHTI210620
Derevitskii I., Savitskaya D.A., Babenko A.Y., Kovalchuk S.V. Hybrid predictive modelling: Thyrotoxic atrial fibrillation case. Journal of Computational Science. 2021. Vol. 51. pp. 101365.. doi: 10.1016/j.jocs.2021.101365
Balabaeva K.Y., Kovalchuk S.V. Clustering Results Interpretation of Continuous Variables Using Bayesian Inference. Studies in health technology and informatics. 2021. Vol. 281. pp. 477-481.. doi: 10.3233/SHTI210204
Kopanitsa G.D., Derevitckii I.V., Savitskaya D.A., Kovalchuk S. Assessing acceptance level of a hybrid clinical decision support systems. Studies in health technology and informatics. 2021. Vol. 287. pp. 18-22.. doi: 10.3233/SHTI210802
Mramorov N., Derevitskii I., Kovalchuk S. Predictive modeling of COVID and nonCOVID pneumonia trajectories. Studies in health technology and informatics. 2021. Vol. 285. pp. 112-117.. doi: 10.3233/SHTI210582
Kopanitsa G.D., Metsker O., Bolgova E.V., Kovalchuk S. Lifestyle cancer survival predictors: Influence of vegetarian diet on the relapse of endometrial cancer. Studies in health technology and informatics. 2021. Vol. 285. pp. 193-198.. doi: 10.3233/SHTI210597
Funkner A.A., Zhurman D., Kovalchuk S. Extraction of Temporal Structures for Clinical Events in Unlabeled Free-Text Electronic Health Records in Russian. Studies in health technology and informatics. 2021. Vol. 287. pp. 55-56.. doi: 10.3233/SHTI210811
Методы и технологии масштабируемости алгоритмов интеллектуального анализа медицинских текстов
Разработка системы мультиагентного имитационного моделирования бизнес-процессов в крупной компании
Abuhay T.M., Robinson S., Mamuye A., Kovalchuk S.V. Why machine learning integrated patient flow simulation?. 10th Operational Research Society Simulation Workshop, SW 2021. 2021. pp. 375-384.. doi: 10.36819/SW21.041
Kshenin A.D., Kovalchuk S. Data-driven modeling of complex business process in heterogeneous environment of healthcare organization with health information systems. Studies in health technology and informatics. 2021. Vol. 285. pp. 118-123.. doi: 10.3233/SHTI210583
Nikolaeva K., Elkhovskaya L., Kovalchuk S. Patient measurements simulation and event processing in telemedicine systems. Procedia Computer Science. 2021. Vol. 193. pp. 122-130.. doi: 10.1016/j.procs.2021.10.012
Koshman V., Funkner A.A., Kovalchuk S. An unsupervised approach to structuring and analyzing repetitive semantic structures in free text of electronic medical records. Studies in health technology and informatics. 2021. Vol. 285. pp. 94-99.. doi: 10.3233/SHTI210579
Balabaeva K.Y., Kovalchuk S. Comparison of Efficiency, Stability and Interpretability of Feature Selection Methods for Multiclassification Task on Medical Tabular Data. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 2021. Vol. 12744. pp. 623-633.. doi: 10.1007/978-3-030-77967-2_51
Kanonirov A., Balabaeva K.Y., Kovalchuk S. Statistical inference for clustering results interpretation in clinical practice. Studies in health technology and informatics. 2021. Vol. 285. pp. 100-105.. doi: 10.3233/SHTI210580
Kovalchuk S.V., Krzhizhanovskaya V.V. ., Paszynski M., Zavodszky G., Lees M.H., Dongarra J., Sloot P. 20 years of computational science: Selected papers from 2020 International Conference on Computational Science. Journal of Computational Science. 2021. Vol. 53. pp. 101395.. doi: 10.1016/j.jocs.2021.101395
Funkner A.A., Egorov M., Fokin S.A., Orlov G., Kovalchuk S. Citywide quality of health information system through text mining of electronic health records. Applied Network Science. 2021. Vol. 6. No. 1. pp. 53.. doi: 10.1007/s41109-021-00395-2
Ponomartseva D., Derevitckii I.V., Kovalchuk S., Babenko A. Prediction model for thyrotoxic atrial fibrillation: a retrospective study. BMC Endocrine Disorders. 2021. Vol. 21. No. 1. pp. 150.. doi: 10.1186/s12902-021-00809-3
Elkhovskaya L., Kovalchuk S. Feature Engineering with Process Mining Technique for Patient State Predictions. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 2021. Vol. 12744. pp. 584-592.. doi: 10.1007/978-3-030-77967-2_48
Pavlovskii V., Derevitckii I.V., Kovalchuk S. Hybrid Predictive Modelling for Finding Optimal Multipurpose Multicomponent Therapy. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 2021. Vol. 12744. pp. 479-793.. doi: 10.1007/978-3-030-77967-2_40
Бухановский А.В., Иванов С.В., Ковальчук С.В., Нечаев Ю.И. Онтологическая система знаний и вычислительных ресурсов современных интеллектуальных технологий. Онтология проектирования. 2020. Т. 10. № 1(35). С. 22-33.. doi: 10.18287/2223-9537-2020-10-1-22-33
Balabaeva K., Kovalchuk S.V. Experiencer detection and automated extraction of a family disease tree from medical texts in russian language. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 2020. Vol. 12140 LNCS. pp. 603-612.. doi: 10.1007/978-3-030-50423-6_45
Balabaeva K.Y., Funkner A., Kovalchuk S. Automated Spelling Correction for Clinical Text Mining in Russian. Studies in health technology and informatics. 2020. Vol. 270. pp. 43-47.. doi: 10.3233/SHTI200119
Abuhay T.M., Metsker O.G., Yakovlev A.N., Kovalchuk S.V. Constructing holistic patient flow simulation using system approach. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 2020. Vol. 12140 LNCS. pp. 418-429.. doi: 10.1007/978-3-030-50423-6_31
Bolgova K.V., Kovalchuk S.V., Balakhontceva M.A., Zvartau N.E., Metsker O.G. Human Computer Interaction During Clinical Decision Support With Electronic Health Records Improvement. International Journal of E-Health and Medical Communications. 2020. Vol. 11. No. 1. pp. 93-106.. doi: 10.4018/IJEHMC.2020010106
Derevitckii I.V., Kovalchuk S.V. Machine Learning-Based Predictive Modeling of Complications of Chronic Diabetes. Procedia Computer Science. 2020. Vol. 178. pp. 274-283.. doi: 10.1016/j.procs.2020.11.029
Leonenko V.N., Kovalchuk S.V. Analyzing the spatial distribution of individuals predisposed to arterial hypertension in Saint Petersburg using synthetic populations. ITM Web of Conferences. 2020. Vol. 31. pp. 03002.. doi: 10.1051/itmconf/20203103002
Balabaeva K.Y., Kovalchuk S.V. Post-hoc Interpretation of Clinical Pathways Clustering using Bayesian Inference. Procedia Computer Science. 2020. Vol. 178. pp. 264-273.. doi: 10.1016/j.procs.2020.11.028
Kovalchuk S.V., Krzhizhanovskaya V.V., Sloot P. 20 years of computational Science. Journal of Computational Science. 2020. Vol. 46. pp. 101187.. doi: 10.1016/j.jocs.2020.101187
Моделирование бизнес-процессов с высоким влиянием человеческого фактора на разнородных данных корпоративных информационных систем
Обработка медицинских текстов на естественном языке
Семантический анализ корпусов текстов с помощью методов тематического моделирования
Kovalchuk S.V., Funkner A.A., Balabaeva K.Y., Derevitskii I.V., Fonin V.V., Bukhanov N.V. Towards Modeling of Information Processing Within Business-Processes of Service-Providing Organizations. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 2020. Vol. 12137 LNCS. pp. 667-675.. doi: 10.1007/978-3-030-50371-0_49
Abuhay T.M., Nigatie Y.G., Metsker O., Yakovlev A.N., Kovalchuk S.V. Investigating coordination of hospital departments in delivering healthcare for acute coronary syndrome patients using data-driven network analysis. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 2020. Vol. 12140 LNCS. pp. 430-440.. doi: 10.1007/978-3-030-50423-6_32
Derevitskii I.V., Savitskaya D.A., Babenko A.Y., Kovalchuk S.V. The atrial fibrillation risk score for hyperthyroidism patients. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 2020. Vol. 12140 LNCS. pp. 495-508.. doi: 10.1007/978-3-030-50423-6_37
Metsker O., Magoev K., Yakovlev A., Yanishevskiy S., Kopanitsa G., Kovalchuk S., Krzhizhanovskaya V.V. Identification of risk factors for patients with diabetes: diabetic polyneuropathy case study. BMC Medical Informatics and Decision Making. 2020. Vol. 20. No. 1. pp. 201.. doi: 10.1186/s12911-020-01215-w
Derevitskii I.V., Kovalchuk S.V. . Machine Learning-Based Factor Analysis of Carbohydrate Metabolism Compensation for TDM2 Patients. Studies in health technology and informatics. 2020. Vol. 273. pp. 123-128.. doi: 10.3233/SHTI200626
Guleva V.Y., Shikov E., Bochenina K.O., Kovalchuk S.V., Alodjants A.P., Bukhanovsky A.V. . Emerging complexity in distributed intelligent systems. Entropy. 2020. Vol. 22. No. 12. pp. 1437.. doi: 10.3390/e22121437
Balabaeva K.Y., Akmadieva L., Kovalchuk S.V. Optimal Wells Placement to Maximize the Field Coverage Using Derivative-Free Optimization. Procedia Computer Science. 2020. Vol. 178. pp. 65-74.. doi: 10.1016/j.procs.2020.11.008
Bukhanov N.V., Trudkov P., Vinogradova E., Derevitckii I.V., Balabaeva K.I., Funkner A., Kovalchuk S.V. Computational approach for data-driven mining of upstream value-added structures. EAGE/AAPG Digital Subsurface for Asia Pacific Conference 2020. 2020. pp. 1-5.. doi: 10.3997/2214-4609.202075009
Funkner A., Balabaeva K., Kovalchuk S. Negation Detection for Clinical Text Mining in Russian. Studies in health technology and informatics. 2020. Vol. 270. pp. 342-346.. doi: 10.3233/SHTI200179
Funkner A.A., Kovalchuk S.V. Time Expressions Identification Without Human-Labeled Corpus for Clinical Text Mining in Russian. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 2020. Vol. 12140 LNCS. pp. 591-602.. doi: 10.1007/978-3-030-50423-6_44
Derevitskii I.V., Kovalchuk S.V. Analysis course of the disease of type 2 diabetes patients using Markov chains and clustering methods. Procedia Computer Science. 2019. Vol. 156. pp. 114-122.. doi: 10.1016/j.procs.2019.08.186
Balabaeva K.I., Kovalchuk S.V., Metsker O. Dynamic features impact on the quality of chronic heart failure predictive modelling. Studies in health technology and informatics. 2019. Vol. 261. pp. 179-184.. doi: 10.3233/978-1-61499-975-1-179
Metsker O., Yakovlev A., Ilin A.E., Kovalchuk S.V. Echocardiography Population Study in Russian Federation for 4P Medicine Using Machine Learning. Studies in health technology and informatics. 2019. Vol. 261. pp. 137-142.. doi: 10.3233/978-1-61499-975-1-137
Metsker O., Trofimov E., Sikorskiy S., Kovalchuk S.V. Text and Data Mining Techniques in Judgment Open Data Analysis for Administrative Practice Control. Communications in Computer and Information Science. 2019. Vol. 947. pp. 169-180.. doi: 10.1007/978-3-030-13283-5_13
Ionov M., Zvartau N., Semakova A.A., Bolgova E., Kovalchuk S.V., Boukhanovsky A.V., Konradi A.O. Response rate and patients characteristics associated with effective antihypertensive monotherapy. Journal of Hypertension. 2019. Vol. 37. pp. E105.. doi: 10.1097/01.hjh.0000571352.43815.03
Mikhailov Y.I., Budrin A.G., Budrina E.V., Kovalchuk S.V., Soldatova A.V., Lemeshkin R.N. Informational Support of Automated Quality Management Systems for Medical Service Provision Based on the Prognosis of the Patient Affects Outcome in Social Emergencies. 2019 IEEE International Conference "Quality Management, Transport and Information Security, Information Technologies" (IT&QM&IS). 2019. pp. 284-287.. doi: 10.1109/ITQMIS.2019.8928385
Elkhovskaya L., Kabyshev M., Funkner A., Balakhontceva M., Fonin V., Kovalchuk S. Personalized Assistance for Patients with Chronic Diseases Through Multi-Level Distributed Healthcare Process Assessment. Studies in health technology and informatics. 2019. Vol. 261. pp. 309-312.. doi: 10.3233/978-1-61499-975-1-309
Kabyshev M.V., Kovalchuk S.V. . Development of personalized mobile assistant for chronic disease patients: diabetes mellitus case study. Procedia Computer Science. 2019. Vol. 156. pp. 123-133.. doi: 10.1016/j.procs.2019.08.187
Derevitskii I., Funkner A., Kovalchuk S., Metsker O. Graph-Based Predictive Modelling of Chronic Disease Development: Type 2 DM Case Study. Studies in health technology and informatics. 2019. Vol. 261. pp. 150-155.. doi: 10.3233/978-1-61499-975-1-150
Kovalchuk S.V., Krzhizhanovskaya V.V. ., Shi Y., Fu H., Lees M.H., Dongarra J., Sloot P. Science at the Intersection of Data, Modelling, and Computation. Journal of Computational Science. 2019. Vol. 34. pp. 117-119.. doi: 10.1016/j.jocs.2019.05.005
Balabaeva K., Kovalchuk S.V. Comparison of Temporal and Non-Temporal Features Effect on Machine Learning Models Quality and Interpretability for Chronic Heart Failure Patients. Procedia Computer Science. 2019. Vol. 156. pp. 87-96.. doi: 10.1016/j.procs.2019.08.183
Metsker O., Kesarev S., Bolgova E., Golubev K., Karsakov A., Yakovlev A., Kovalchuk S. Modelling and Analysis of Complex Patient-Treatment Process Using GraphMiner Toolbox. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 2019. Vol. 11540 LNCS. pp. 674-680.. doi: 10.1007/978-3-030-22750-0_65
Функнер А.А., Ковальчук С.В. Суррогатная настройка эволюционных моделей на примере метода идентификации клинических путей. Международная школа-конференция "Высокопроизводительные вычисления и искусственный интеллект"". 2019.
Metsker O.G., Sikorskiy S.A., Semakova A.A., Krikunov A., Balakhontceva M.A., Melnikova N.B., Kovalchuk S.V. Holistic Monitoring and Analysis of Healthcare Processes through Public Internet Data Collection. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 2019. Vol. 11551. pp. 42-50.. doi: 10.1007/978-3-030-17705-8_4
Nikitin N.O., Deeva I., Vychuzhanin P., Kalyuzhnaya A.V., Hvatov A., Kovalchuk S.V. Deadline-driven approach for multi-fidelity surrogate-assisted environmental model calibration: SWAN wind wave model case study. GECCO 2019 - Proceedings of the 2019 Genetic and Evolutionary Computation Conference Companion. 2019. pp. 1583-1591.. doi: 10.1145/3319619.3326876
Funkner A.A., Zvartau N.E., Kovalchuk S.V. Motif identification in vital signs of chronic patients. Procedia Computer Science. 2019. Vol. 156. pp. 105-113.. doi: 10.1016/j.procs.2019.08.185
Kovalchuk S.V., Moskalenko M.A., Yakovlev A.N. Towards Model-based Policy Elaboration on City Scale using Game Theory: Application to Ambulance Dispatching. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 2018. Vol. 10860. pp. 404-417.. doi: 10.1007/978-3-319-93698-7_31
Kovalchuk S.V. ., Funkner A.A., Metsker O.G., Yakovlev A.N. Simulation of Patient Flow in multiple Healthcare Units using Process and Data Mining Techniques for Model Identification. Journal of Biomedical Informatics. 2018. Vol. 82. pp. 128-142.. doi: 10.1016/j.jbi.2018.05.004
Sikorskiy S., Metsker O., Yakovlev A., Kovalchuk S. Machine Learning Based Text Mining in Electronic Health Records: Cardiovascular Patient Cases. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 2018. Vol. 10862. pp. 818-824.. doi: 10.1007/978-3-319-93713-7_80
Fu X., Presbitero A., Kovalchuk S.V., Krzhizhanovskaya V.V. Coupling Game Theory and Discrete-Event Simulation for Model-Based Ambulance Dispatching. Procedia Computer Science. 2018. Vol. 136. pp. 398-407.. doi: 10.1016/j.procs.2018.08.274
Magoev K., Krzhizhanovskaya V.V., Kovalchuk S.V. Application of clustering methods for detecting critical acute coronary syndrome patients. Procedia Computer Science. 2018. Vol. 136. pp. 370-379.. doi: 10.1016/j.procs.2018.08.277
Kovalchuk S.V., Kisliakovskii I.O., Metsker O.G., Nikitin N.O., Funkner A.A., Kalyuzhnaya A.V., Vaganov D.A., Bochenina K.O. Towards management of complex modeling through a hybrid evolutionary identification. GECCO 2018 Companion - Proceedings of the 2018 Genetic and Evolutionary Computation Conference Companion. 2018. pp. 255-256.. doi: 10.1145/3205651.3205751
Butakov N., Petrov M., Mukhina K., Nasonov D.A., Kovalchuk S.V. Unified domain-specific language for collecting and processing data of social media. Journal of Intelligent Information Systems. 2018. Vol. 51. No. 2. pp. 389-414.. doi: 10.1007/s10844-018-0508-5
Metsker O., Yakovlev A., Bolgova E.V., Vasin A., Kovalchuk S. Identification of Pathophysiological Subclinical Variances During Complex Treatment Process of Cardiovascular Patients. Procedia Computer Science. 2018. Vol. 138. pp. 161-168.. doi: 10.1016/j.procs.2018.10.023
Лемешкин Р.Н., Савченко И., Латыпов И.Ф., Жуков А., Крикунов А.В., Ковальчук С.В., Балахонцева М.А. Имитационное моделирование - инструмент научного изучения организации медицинского обеспечения войск (сил) в военных конфликтах и чрезвычайных ситуациях мирного времени. Медицина катастроф [Medicina Katastrof]. 2018. № 2(102). С. 5-10.
Abuhay T.M., Nigatie Y.G., Metsker O.G., Kovalchuk S.V. . Investigating Application of Change Point Analysis in Monitoring Health Condition of Acute Coronary Syndrome Patients. Procedia Computer Science. 2018. Vol. 136. pp. 408-415.. doi: 10.1016/j.procs.2018.08.273
Абухай Т., Ковальчук С.В., Балахонцева М.А., Бухановский А.В. Моделирование, анализ и прогнозирование процессов оказания кардиологической помощи в стационаре. Известия высших учебных заведений. Приборостроение. 2018. Т. 61. № 8. С. 730-733.. doi: 10.17586/0021-3454-2018-61-8-730-733
Kovalchuk S.V. ., Krotov E., Smirnov P.A. ., Nasonov D.A. ., Yakovlev A.N. Distributed Data-Driven Platform for Urgent Decision Making in Cardiological Ambulance Control. Future Generation Computer Systems. 2018. Vol. 79. No. Part.1. pp. 144-154.. doi: 10.1016/j.future.2016.09.017
Zvartau N., Semakova A., Bolgova E., Kovalchuk S., Boukhanovsky A., Konradi A. Prediction Of Blood Pressure-lowering Efficacy Of Antihypertensive Treatment Depending On Individual Patient Characteristics: Initial Model. Journal of Hypertension. 2018. Vol. 36. No. Suppl.1. pp. e21.. doi: 10.1097/01.hjh.0000539019.52393.9c
Балахонцева М.А., Ковальчук С.В., Ховричев М.А., Кисляковский И.О. Интеллектуальная интеграция разнородных источников данных в задачах медицины и здравоохранения. Международная конференция по мягким вычислениям и измерениям. 2018. Т. 2. С. 31-33.
Kovalchuk S.V. ., Metsker O.G., Funkner A.A., Kisliakovskii I.O., Nikitin N.O., Kalyuzhnaya A.V., Vaganov D.A., Bochenina K.O. A Conceptual Approach to Complex Model Management with Generalized Modelling Patterns and Evolutionary Identification. Complexity. 2018. pp. 5870987.. doi: 10.1155/2018/5870987
Balakhontceva M.A., Funkner A.A., Semakova A.A., Metsker O.G., Zvartau N.E., Yakovlev A.N., Lutsenko A.E., Kovalchuk S.V. Holistic Modeling of Chronic Diseases for Recommendation Elaboration and Decision Making. Procedia Computer Science. 2018. Vol. 138. pp. 228-237.. doi: 10.1016/j.procs.2018.10.033
Metsker O., Sikorsky S., Yakovlev A., Kovalchuk S. Dynamic mortality prediction using machine learning techniques for acute cardiovascular cases. Procedia Computer Science. 2018. Vol. 136. pp. 351-358.. doi: 10.1016/j.procs.2018.08.279
Abuhay T.M., Nigatie Y.G., Kovalchuk S.V. Towards Predicting Trend of Scientific Research Topics using Topic Modeling. Procedia Computer Science. 2018. Vol. 136. pp. 304-310.. doi: 10.1016/j.procs.2018.08.284
Vaganov D., Funkner A., Kovalchuk S., Guleva V., Bochenina K. Forecasting Purchase Categories with Transition Graphs Using Financial and Social Data. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 2018. Vol. 11185. pp. 439-454.. doi: 10.1007/978-3-030-01129-1_27
Kovalchuk S.V., Krzhizhanovskaya V.V., Koumoutsakos P., Chatzi E., Lees M.H., Dongarra J., Sloot P.M. The Art of Computational Science: Bridging Gaps – Forming Alloys. Journal of Computational Science. 2018. Vol. 26. pp. 190-192.. doi: 10.1016/j.jocs.2018.04.014
Yakovlev A., Metsker O., Kovalchuk S.V., Bologova E. Prediction of in-hospital mortality and length of stay in acute coronary syndrome patients using machine-learning methods. Journal of the American College of Cardiology. 2018. Vol. 71. No. 11(Suppl.). pp. A242.. doi: 10.1016/S0735-1097(18)30783-6
Abuhay T.M., Kovalchuk S.V., Bochenina K.O., Mbogo G., Visheratin A.A., Kampis G., Krzhizhanovskaya V.V., Lees M.H. Analysis of Publication Activity of Computational Science Society in 2001-2017 Using Topic Modelling and Graph Theory. Journal of Computational Science. 2018. Vol. 26. pp. 193-204.. doi: 10.1016/j.jocs.2018.04.004
Семакова А.А., Звартау Н.Э., Ковальчук С.В., Бухановский А.В. Многомасштабное популяционное моделирование процессов развития и лечения артериальной гипертензии. Известия высших учебных заведений. Приборостроение. 2018. Т. 61. № 10. С. 922-929.. doi: 10.17586/0021-3454-2018-61-10-922-929
Производственная (научно-исследовательская) и производственная (преддипломная) практика студентов: организация и проведение
Производственная (научно-исследовательская) и производственная (преддипломная) практика студентов: организация и проведение
Zvartau N., Krikunov A., Semakova A., Bolgova E., Kovalchuk S., Boukhanovsky A., Konradi A. Antihypertensive treatment in routine clinical practice of specialized cardiological centre: six-years trends. Journal of Hypertension. 2017. Vol. 35. No. e-Supplement 2. pp. e93-e93.
Zvartau N., Krikunov A., Semakova A., Bolgova E., Kovalchuk S., Boukhanovsky A., Konradi A. Six-year trends in antyhypertensive monotherapy and blood pressure control in patients referred to specialized cardiological centre. Journal of Hypertension. 2017. Vol. 35. No. e-Supplement 2. pp. e102-e102.
МЕТОДИЧЕСКИЕ РЕКОМЕНДАЦИИ ПО ВЫПОЛНЕНИЮ ЛАБОРАТОРНЫХ РАБОТ ПО ДИСЦИПЛИНЕ «МАТЕМАТИЧЕСКИЕ МЕТОДЫ КОМПЛЕКСОВ ПРОГРАММ»
Имитационное моделирование нагрузки на группу ключевых отделений специализированного медицинского центра в ходе обслуживания разнородного потока пациентов на примере острого коронарного синдрома
Funkner A.A., Yakovlev A.N., Kovalchuk S.V. . Towards Evolutionary Discovery of Typical Clinical Pathways in Electronic Health Records. Procedia Computer Science. 2017. Vol. 119. pp. 234-244.. doi: 10.1016/j.procs.2017.11.181
Metsker O.G., Bolgova E.V., Yakovlev A.N., Funkner A.A., Kovalchuk S.V. . Pattern-based Mining in Electronic Health Records for Complex Clinical Process Analysis. Procedia Computer Science. 2017. Vol. 119. pp. 197-206.. doi: 10.1016/j.procs.2017.11.177
Abuhay T.M., Kovalchuk S.V. ., Bochenina K.O., Kampis G., Krzhizhanovskaya V.V. ., Lees M.H. Analysis of Computational Science Papers from ICCS 2001-2016 using Topic Modeling and Graph Theory. Procedia Computer Science. 2017. Vol. 108. pp. 7-17.. doi: 10.1016/j.procs.2017.05.183
Palomares I., Kovalchuk S.V. . Multi-View Data approaches in Recommender Systems: an Overview: (Invited Paper). Procedia Computer Science. 2017. Vol. 119. pp. 30-41.. doi: 10.1016/j.procs.2017.11.157
Chirkin A.M., Belloum A., Kovalchuk S.V., Makkes M., Melnik M.A., Visheratin A.A., Nasonov D.A. Execution Time Estimation for Workflow Scheduling. Future Generation Computer Systems. 2017. Vol. 75. pp. 376-387.. doi: 10.1016/j.future.2017.01.011
Kovalchuk S.V. ., Funkner A., Metsker O., Yakovlev A. Data-driven modeling and simulation of complex healthcare environment for p4 medicine. Исследования по геоинформатике: труды геофизического центра РАН. 2017. Vol. 5. No. 1. pp. 144.. doi: 10.2205/CODATA2017
Kovalchuk S.V., Krikunov A.V., Knyazkov K.V., Boukhanovsky A.V. Classification issues within ensemble-based simulation: application to surge floods forecasting. Stochastic Environmental Research and Risk Assessment. 2017. Vol. 31. No. 5. pp. 1183-1197.. doi: 10.1007/s00477-016-1324-5
Derevitskiy I., Krotov E., Voloshin D., Yakovlev A., Kovalchuk S.V., Karbovskii V. Simulation of emergency care for patients with ACS in Saint Petersburg for ambulance decision making. Procedia Computer Science. 2017. Vol. 108. pp. 2210-2219.. doi: 10.1016/j.procs.2017.05.178
Zvartau N., Krikunov A., Semakova A., Bolgova E., Kovalchuk S., Boukhanovsky A., Konradi A. Six-year trends in antihypertensive monotherapy: focus on blood pressure control and originals/generics ratio. European heart journal. 2017. Vol. 38. No. Suppl. 1. pp. 359-359.
Kashirin V.V. ., Lantseva A.A., Ivanov S.V., Kovalchuk S.V. ., Boukhanovsky A.V. Evolutionary simulation of complex networks' structures with specific functional properties. Journal of Applied Logic. 2017. Vol. 24. pp. 39-49.. doi: 10.1016/j.jal.2016.11.012
Лемешкин Р.Н., Крикунов А.В., Ковальчук С.В., Савченко И. Имитационная модель оказания медицинской помощи раненым в медицинском отряде специального назначения в ходе ликвидации медико-санитарных последствий чрезвычайных ситуаций. Медико-биологические и социально-психологические проблемы безопасности в чрезвычайных ситуациях [Medico-Biological and Socio-Psychological Issues of Safety in Emergency Situations]. 2017. № 4. С. 20-33.. doi: 10.25016/2541-7487-2017-0-4-20-33
Funkner A., Yakovlev A., Kovalchuk S.V. . Data-driven modeling of clinical pathways using electronic health records. Procedia Computer Science. 2017. Vol. 121. pp. 835-842.. doi: 10.1016/j.procs.2017.11.108
Kisliakovskii I., Balakhontceva M., Kovalchuk S., Zvartau N., Konradi A. Towards a simulation-based framework for decision support in healthcare quality assessment. Procedia Computer Science. 2017. Vol. 119. pp. 207-214.. doi: 10.1016/j.procs.2017.11.178
Bolgova E.V., Zvartau N.E., Kovalchuk S., Balakhontceva M., Metsker O.G. Improving Electronic Medical Records with Support of Human Computer Interaction in Medical Information Systems. Procedia Computer Science. 2017. Vol. 121. pp. 469-474.. doi: 10.1016/j.procs.2017.11.063
Функнер А.А., Яковлев А.Н., Ковальчук С.В. Имитационное моделирование нагрузки на группу ключевых отделений специализированного медицинского центра в ходе обслуживания разнородного потока пациентов на примере острого коронарного синдрома. Труды Восьмой Всероссийской научно-практической конференции "Имитационное моделирование. Теория и практика" (ИММОД-2017) (СПб, 18-20октября 2017г.). 2017. С. 550-553.
Bukhanov N., Balakhontceva M., Kovalchuk S., Zvartau N., Konradi A. Multiscale modeling of comorbidity relations in hypertensive outpatients. Procedia Computer Science. 2017. Vol. 121. pp. 446-450.. doi: 10.1016/j.procs.2017.11.060
Kovalchuk S.V., Abuhay T.M., Altintas I., Norman M., Lees M.H., Krzhizhanovskaya V.V., Dongarra J., Sloot P. Data through the Computational Lens. Journal of Computational Science. 2017. Vol. 20. pp. 81-84.. doi: 10.1016/j.jocs.2017.05.003
Funkner A., Kovalchuk S.V., Bochenina K. Preoperational Time Prediction for Percutaneous Coronary Intervention Using Machine Learning Techniques. Procedia Computer Science. 2016. Vol. 101. pp. 172-176.. doi: 10.1016/j.procs.2016.11.021
Zvartau N., Krikunov A., Semakova A., Bolgova E., Kovalchuk S., Boukhanovsky A., Konradi A.O. Five-years trends in demographic chcracteristics of hypertensive patients referred to specialized cardiological centre: age and gender. Journal of Hypertension. 2016. Vol. 34. No. Suppl.2. pp. e62.. doi: 10.1097/01.hjh.0000491498.26078.45
Kiselev A.V., Karbovskii V., Kovalchuk S.V. . Agent-based modelling using ensemble approach with spatial and temporal composition. Procedia Computer Science. 2016. Vol. 80. pp. 530-541.. doi: 10.1016/j.procs.2016.05.333
Abuhay T.M., Krikunov A.V., Bolgova E.V., Ratova L.G., Kovalchuk S.V. Simulation of Patient Flow and Load of Departments in a Specialized Medical Center. Procedia Computer Science. 2016. Vol. 101. pp. 143–151.. doi: 10.1016/j.procs.2016.11.018
Karsakov A., Moiseev A., Mukhina K., Ankudinova I., Ignatieva M., Krotov E., Karbovskii V., Kovalchuk S., Konradi A. Toolbox for Visual Explorative Analysis of Complex Temporal Multiscale Contact Networks Dynamics in Healthcare. Procedia Computer Science. 2016. Vol. 80. pp. 2107-2118.. doi: 10.1016/j.procs.2016.05.530
Syomov I.I., Bolgova E.V., Kovalchuk S.V., Krikunov A.V., Moiseeva O.M., Simakova M.A. Towards Infrastructure for Knowledge-based Decision Support in Clinical Practice. Procedia Computer Science. 2016. Vol. 100. pp. 907–914.. doi: 10.1016/j.procs.2016.09.242
Zvartau N., Krikunov A.V., Semakova A.A., Bolgova E.V., Kovalchuk S.V. ., Bukhanovsky A.V. . Five-year trends in specific risk factors in hypertensive patients reffered to specialized cardiological centre. European heart journal. 2016. Vol. 37. No. Suppl.1. pp. 66-67.
Krikunov A.V., Bolgova E.V., Krotov V., Abukhai T., Yakovlev A.N., Kovalchuk S.V. Complex data-driven predictive modeling in personalized clinical decision support for acute coronary syndrome episodes. Procedia Computer Science. 2016. Vol. 80. pp. 518-529.. doi: 10.1016/j.procs.2016.05.332
Zvartau N., Krikunov A., Semakova A., Bolgova E., Kovalchuk S., Boukhanovsky A., Konradi A.O. Prevalence of diabetes and lipid disorders in hypertension patients referred to specialized cardiological centre: five-years trends. Journal of Hypertension. 2016. Vol. 34. No. Suppl.2. pp. e322-e323.. doi: 10.1097/01.hjh.0000492288.56134.f4
Bolgova E.V., Prokusheva D.I., Krikunov A.V., Zvartau N.E., Kovalchuk S.V. Human-Computer Interaction in Electronic Medical Records: From the Perspectives of Physicians and Data Scientists. Procedia Computer Science. 2016. Vol. 100. pp. 915–920.. doi: 10.1016/j.procs.2016.09.248
Zakharchuk A.V., Kovalchuk S.V., Nasonov D.A. Dynamic domain-specific language for BigData tasks' description. Lecture Notes in Informatics (LNI), Proceedings - Series of the Gesellschaft fur Informatik (GI). 2015. Vol. 246. pp. 1207-1218.
Nasonov D.A. ., Visheratin A.A., Knyazkov K.V., Kovalchuk S.V. Interactive e-Science Cyberinfrastructure for Workflow Management Coupled with Big Data Technology. International Multidisciplinary Scientific GeoConference-SGEM: 15th International Multidisciplinary Scientific Geoconference SGEM 2015. 2015. Vol. 1. No. 2. pp. 175-182.. doi: 10.5593/SGEM2015/B21/S7.023
Kovalchuk S.V., Boukhanovsky A.V. Towards Ensemble Simulation of Complex Systems. Procedia Computer Science. 2015. Vol. 51. pp. 532-541.. doi: 10.1016/j.procs.2015.05.280
Kovalchuk S.V., Knyazkov K.V., Syomov I.I., Yakovlev A.N., Boukhanovsky A.V. Personalized Clinical Decision Support with Complex Hospital-Level Modelling. Procedia Computer Science. 2015. Vol. 66. pp. 392-401.. doi: 10.1016/j.procs.2015.11.045
Kosukhin S.S., Kovalchuk S.V., Boukhanovsky A.V. Cloud Technology for Forecasting Accuracy Evaluation of Extreme Metocean Events. Procedia Computer Science. 2015. Vol. 51. pp. 2933-2937.. doi: 10.1016/j.procs.2015.05.483
Krikunov A.V., Kovalchuk S.V. . Dynamic Selection of Ensemble Members in Multi-model Hydrometeorological Ensemble Forecasting. Procedia Computer Science. 2015. Vol. 66. pp. 220-227.. doi: 10.1016/j.procs.2015.11.026
Smirnov P.A., Kovalchuk S.V. Linked-Data Integration for Workflow-Based Computational Experiments. Communications in Computer and Information Science. 2014. Vol. 468. pp. 175-183.. doi: 10.1007/978-3-319-11716-4_15
Kovalchuk S.V. ., Zakharchuk A.V., Liao J., Ivanov S.V. ., Boukhanovsky A.V. . A Technology for BigData Analysis Task Description using Domain-Specific Languages. Procedia Computer Science. 2014. Vol. 29. pp. 488–498.. doi: 10.1016/j.procs.2014.05.044
Knyazkov K.V. ., Kovalchuk S.V. . Modeling and Simulation Framework for Development of Interactive Virtual Environments. Procedia Computer Science. 2014. Vol. 29. pp. 332–342.. doi: 10.1016/j.procs.2014.05.030
Kovalchuk S.V., Bezgodov A.A., Terekhov D.M., Boukhanovsky A.V. Interactive Environment for Affective Visual Analysis of Large Data within Virtual Reality. Proceedings of 2014 Science and Information Conference. 2014. pp. 736-741.. doi: 10.1109/SAI.2014.6918269
Dukhanov A.V., Smirnov P.A., Karpova M.S., Kovalchuk S.V. e-Learning Course Design Based on the Virtual Simulation Objects Concept. 8th IEEE International Conference on Application of Information and Communication Technologies, AICT 2014 - Conference Proceedings. 2014. pp. 7036016.. doi: 10.1109/ICAICT.2014.7036016
Kovalchuk S.V., Smirnov P.A., Knyazkov K.V., Zagarskikh A.S., Boukhanovsky A.V. Knowledge-based Expressive Technologies within Cloud Computing Environments. Advances in Intelligent Systems and Computing. 2014. Vol. 279. pp. 1-11.. doi: 10.1007/978-3-642-54927-4_1
Smirnov P.A., Kovalchuk S.V. Provenance-Based Workflow Composition with Virtual Simulation Objects Technology. 2014 11th International Conference on Fuzzy Systems and Knowledge Discovery, FSKD 2014. 2014. pp. 930-934.. doi: 10.1109/FSKD.2014.6980964
Smirnov P.A., Kovalchuk S.V., Dukhanov A.V. Domain Ontologies Integration for Virtual Modelling and Simulation Environments. Procedia Computer Science. 2014. Vol. 29. pp. 2507 -2514.. doi: 10.1016/j.procs.2014.05.234
Kashirin V.V., Kovalchuk S.V., Boukhanovsky A.V. Evolutionary simulation of complex networks’ structures with specific functional properties. Advances in Intelligent Systems and Computing. 2014. Vol. 299. pp. 63-72.. doi: 10.1007/978-3-319-07995-0.7
Chirkin A.M. ., Kovalchuk S.V. Towards Better Workflow Execution Time Estimation. IERI Procedia. 2014. Vol. 10. pp. 216–223.. doi: 10.1016/j.ieri.2014.09.080
Nasonov D.A., Churov T.N., Zagarskikh A.S., Kovalchuk S.V. Technological platform for complex processing of large data within early warning systems. WIT Transactions on Information and Communication Technologies. 2014. Vol. 56. pp. 625-634.. doi: 10.2495/ICCTS140711
Chirkin A.M. ., Belloum A., Kovalchuk S.V., Makkes M. Execution Time Estimation for Workflow Scheduling. Proceedings of WORKS 2014: The 9th Workshop on Workflows in Support of Large-Scale Science - held in conjunction with SC 2014: The International Conference for High Performance Computing, Networking, Storage and Analysis. 2014. pp. 7019857.. doi: 10.1109/WORKS.2014.11
Динамический предметно-ориентированный язык для задач распределенной обработки больших данных в средах облачных вычислений
Kovalchuk S.V., Terekhov D.M., Bezgodov A.A., Boukhanovsky A.V. Visual Exploration of Complex Network Data Using Affective Brain-Computer Interface. International Journal of Advanced Computer Science and Applications (IJACSA). 2013. Vol. 4. No. 7. pp. 21–27.
Kovalchuk S.V., Smirnov P.A., Maryin S.V., Tchurov T.N., Karbovsky V.A. Deadline-driven resource management within urgent computing cyberinfrastructure. Procedia Computer Science. 2013. Vol. 18. pp. 2203 – 2212.. doi: 10.1016/j.procs.2013.05.391
Ковальчук С.В., Чиркин А.М., Князьков К.В. Методы построения и использования моделей производительности облачных сервисов. Динамика сложных систем - XXI век. 2013. Т. 7. № 3. С. 90-94.
Smirnov P.A. ., Kovalchuk S.V., Boukhanovsky A.V. . Knowledge-based support for complex systems exploration in distributed problem solving environments. Communications in Computer and Information Science. 2013. Vol. 394. pp. 147-161.. doi: 10.1007/978-3-642-41360-5_12
Ivanov S.V., Kovalchuk S.V., Boukhanovsky A.V. Workflow-based Collaborative Decision Support for Flood Management Systems. Procedia Computer Science. 2013. Vol. 18. pp. 2213 – 2222.. doi: 10.1016/j.procs.2013.05.392
Boukhanovsky, A.V. ., Kovalchuk S.V. . High-Level Knowledge-Based Structures for Simulation within Urgent Computing Tasks. Procedia Computer Science. 2012. Vol. 9. pp. 1694-1703.. doi: 10.1016/j.procs.2012.04.187
Knyazkov K.V., Kovalchuk S.V., Tchurov T.N., Maryin S.V., Boukhanovsky A.V. CLAVIRE: e-Science Infrastructure for Data-driven Computing. Journal of Computational Science. 2012. Vol. 3. No. 6. pp. 504–510.. doi: 10.1016/j.jocs.2012.08.006
Kovalchuk S.V., Smirnov P.A., Kosukhin S.S., Boukhanovsky A.V. Virtual Simulation Objects Concept as a Framework for System-Level Simulation. 2012 IEEE 8th International Conference on E-Science, e-Science 2012. 2012. pp. 6404413.. doi: 10.1109/eScience.2012.6404413
Марьин С.В., Ковальчук С.В. Сервисно-ориентированная платформа исполнения композитных приложений в распределенной среде. Известия высших учебных заведений. Приборостроение. 2011. Т. 54. № 10. С. 21-29.
Ковальчук С.В., Маслов В.Г. Интеллектуальная поддержка процесса конструирования композитных приложений в распределенных проблемно-ориентированных средах. Известия высших учебных заведений. Приборостроение. 2011. Т. 54. № 10. С. 29-36.
Kovalchuk S.V., Larchenko A., Boukhanovsky A.V. Knowledge-Based Resource Management for Distributed Problem Solving. Advances in Intelligent and Soft Computing. 2011. Vol. 123. pp. 121-128.. doi: 10.1007/978-3-642-25661-5_16
Бухановский А.В., Ковальчук С.В., Марьин С.В., Рыбаков Г.М. Динамическое управление распределенными вычислительными ресурсами в составе композитного приложения. Научно-технический вестник СПбГУ ИТМО. 2010. № 3(67). С. 126-127.
Бухановский А.В., Ковальчук С.В., Марьин С.В. Интеллектуальные высокопроизводительные программные комплексы моделирования сложных систем: концепция, архитектура и примеры реализации. Известия высших учебных заведений. Приборостроение.. 2009. Т. 52. № 10. С. 5–24.
Ковальчук С.В., Бухановский А.В. Параллельная производительность стохастических алгоритмов. Известия высших учебных заведений. Приборостроение. 2008. Т. 51. № 12. С. 5-12.
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