Научные руководители
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Копаница Георгий ДмитриевичPhD, медико-биологические науки kopanitsa@itmo.ru Структурное подразделение: факультет цифровых трансформаций Должность: доцент (квалификационная категория "ординарный доцент") Профиль: 1.2.1. - Искусственный интеллект и машинное обучение 05.13.10 - Управление в социальных и экономических системах 05.13.11 - Математическое и программное обеспечение вычислительных машин, комплексов и компьютерных сетей 2.3.5. - Математическое и программное обеспечение вычислительных систем, комплексов и компьютерных сетей 2.3.8. - Информатика и информационные процессы 1.2.3. - Теоретическая информатика, кибернетика 05.13.18 - Математическое моделирование, численные методы и комплексы программ 05.13.17 - Теоретические основы информатики Область интересов: Теории анализа и синтеза интеллектуальных медицинских информационных систем Моделирование и проектирование интеллектуальных медицинских информационных систем Семантическое моделирование систем Алгоритмы синтеза модели требований и модели классов на основе процессной модели Модальные формализмы и нецелеориентированные стратегии вывода. Область моих научных интересов лежит в оптимизации методов управления в здравоохранении, а именно: Разработка методов формализации и постановка задач управления в социальных и экономических системах. Разработка моделей описания и оценок эффективности решения задач управления и принятия решений в социальных и экономических системах. Разработка методов и алгоритмов решения задач управления и принятия решений в социальных и экономических системах. Рабочий язык: Английский, Немецкий, Русский, Французский |
Публикации руководителя
| Выходные данные | Год | Индексирование в БД |
| Soma G., Kopanitsa G. Development of models for managing the population mass service system in a bank//E3S Web of Conferences, 2024, Vol. 474, pp. 02006 | 2024 | Scopus |
| Guedes S., Kopanitsa G. Development of an emotion and age recognition model based on the combination of local binary patterns and squeeze-and-excitation block method//Proceedings of SPIE, 2024, Vol. 13217, pp. 132170I | 2024 | Scopus, Web of Science |
| 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 | 2023 | Scopus, Web of Science, Белый список |
| Soma G.M., Kopanitsa G.D. System for customers’ routing based on their emotional state and age in public services systems//Научно-технический вестник информационных технологий, механики и оптики [Scientific and Technical Journal of Information Technologies, Mechanics and Optics], 2023, Vol. 23, No. 5(147), pp. 1009-1020 | 2023 | RSCI, Scopus, Белый список, ВАК, РИНЦ |
| 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 | 2022 | Scopus |
| 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 | 2022 | Scopus, Web of Science |
| Gerasimov A., Trofimov E., Kopanitsa G., Metsker O. Modelling Investment Programs with Machine Learning and Data Mining: Descriptive and Predictive Models of Healthcare State Programs in Russia//Proceedings of the 31st Conference of Open Innovations Association FRUCT, 2022, pp. 45-50 | 2022 | Scopus, Web of Science |
| Skiba I., Kopanitsa G., Metsker O., Yanishevskiy S., Polushin A. Application of Machine Learning Methods for Epilepsy Risk Ranking in Patients with Hematopoietic Malignancies Using//Journal of Personalized Medicine, 2022, Vol. 12, No. 8, pp. 1306 | 2022 | Scopus, Web of Science |
| Dubasova E., Berdashkevich A., Kopanitsa G., Kashlikov P., Metsker O. Social Network Users Profiling Using Machine Learning for Information Security Tasks//Proceedings of the 32nd Conference of Open Innovations Association FRUCT, 2022, pp. 87-92 | 2022 | Scopus, Web of Science |
| Irtyuga O., Kopanitsa G., Kostareva A., Metsker O., Uspensky V., Gordeev M., Faggian G., Sefieva G., Derevitskii I., Malashicheva A., Shlyakhto E. Application of Machine Learning Methods to Analyze Occurrence and Clinical Features of Ascending Aortic Dilatation in Patients with and without Bicuspid Aortic Valve//Journal of Personalized Medicine, 2022, Vol. 12, No. 5, pp. 794 | 2022 | Scopus, Web of Science |
| Kopanitsa G. Study of patients' attitude to automatic interpretation of laboratory test results and its influence on follow-up rate//BMC Medical Informatics and Decision Making, 2022, Vol. 22, No. 1, pp. 79 | 2022 | Scopus, Web of Science |
| Lenivtceva I., Panfilov D., Kopanitsa G., Kozlov B. Aortic Risks Prediction Models after Cardiac Surgeries Using Integrated Data//Journal of Personalized Medicine, 2022, Vol. 12, No. 4, pp. 637 | 2022 | Scopus, Web of Science |
| Metsker O., Kopanitsa G.D., Malushko A., Komlichenko E., Bolgova K.V., Paskoshev D. Gynecological Surgery and Machine Learning: Complications and Length of Stay Prediction//Studies in health technology and informatics, 2021, Vol. 281, pp. 575-579 | 2021 | Scopus, Web of Science |
| Metsker O., Trofimov E., Kopanitsa G. Application of machine learning metrics for dynamic E-justice processes//Proceedings of the 28th Conference of Open Innovations Association FRUCT, 2021, pp. 9347598 | 2021 | Scopus, Web of Science |
| Lenivtceva I.D., Grechishcheva S., Kopanitsa G.D., Panfilov D., Kozlov B. Predicting the aortic aneurysm postoperative risks based on Russian integrated data//Studies in health technology and informatics, 2021, Vol. 285, pp. 88-93 | 2021 | Scopus, Web of Science |
| Metsker O., Trofimov E., Kopanitsa G. Application of machine learning for E-justice//Journal of Physics: Conference Series, 2021, Vol. 1828, No. 1, pp. 012006 | 2021 | Scopus, Web of Science |
| Ленивцева Ю.Д., Копаница Г.Д. Определение типа аллергии на основании неструктурированных медицинских записей // Врач и информационные технологии -2021. - № 1. - С. 18-24 | 2021 | RSCI, ВАК, РИНЦ |
| Ленивцева Ю.Д., Копаница Г.Д. Метод сопоставления форматов обмена медицинскими данными и терминологий // Врач и информационные технологии -2021. - № 1. - С. 75-83 | 2021 | RSCI, ВАК, РИНЦ |
| Ленивцева Ю.Д., Копаница Г.Д. Автоматическое определение типа аллергии из неструктурированных медицинских текстов на русском языке [Automatic allergy classification based on russian unstructured medical texts] // Научно-технический вестник информационных технологий, механики и оптики [Scientific and Technical Journal of Information Technologies, Mechanics and Optics] -2021. - Т. 21. - № 3(133). - С. 433-436 | 2021 | RSCI, Scopus, ВАК, РИНЦ |
| Lenivtceva I.D., Kopanitsa G.D. The Pipeline for Standardizing Russian Unstructured Allergy Anamnesis Using FHIR AllergyIntolerance Resource//Methods of Information in Medicine, 2021, Vol. 60, No. 3-4, pp. 95-103 | 2021 | Scopus, Web of Science |
| 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 | 2021 | Scopus, Web of Science |
| Metsker O., Kopanitsa G.D. Influence of Healthcare Organization Factors on Cardiovascular Diseases Mortality//Studies in health technology and informatics, 2021, Vol. 287, pp. 149-152 | 2021 | Scopus, Web of Science |
| Grechishcheva S., Lenivtceva I., Kopanitsa G., Panfilov D. Filtering free-text medical data based on machine learning//Procedia Computer Science, 2021, Vol. 193, pp. 82-91 | 2021 | Scopus, Web of Science |
| Metsker O., Kopanitsa G.D., Irtyuga O., Uspenskiy V. Dynamic aortic aneurism risk factors//Studies in health technology and informatics, 2021, Vol. 285, pp. 130-135 | 2021 | Scopus, Web of Science |
| 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 | 2021 | Scopus, Web of Science |
| Paskoshev D., Kopanitsa G.D., Trofimov E., Metsker O. Simulation of a Judicial Process Using Machine Learning to Analyze Administrative Prejudice and Indicate the Quality of Justice//Proceedings of the 30th Conference of Open Innovations Association FRUCT, 2021, pp. 165-170 | 2021 | Scopus, Web of Science |
| Trofimov E., Metsker O., Kopanitsa G.D., Pashoshev D. Regulation modelling and analysis using machine learning during the Covid-19 pandemic in Russia//Studies in health technology and informatics, 2021, Vol. 285, pp. 259-264 | 2021 | Scopus, Web of Science |
| Kopanitsa G.D., Metsker O., Paskoshev D., Greschischeva S. Identification of Risk Factors and Prediction of Sepsis in Pregnancy Using Machine Learning Methods//Procedia Computer Science, 2021, Vol. 193, pp. 393-401 | 2021 | Scopus, Web of Science |
| Metsker O., Kopanitsa G.D., Yakovlev A., Karlina V., Zvartau N.E. Survival analysis of COVID-19 patients in russia using machine learning//Studies in health technology and informatics, 2020, Vol. 273, pp. 223-227 | 2020 | Scopus, Web of Science |
| Kashina M., Lenivtceva I.D., Kopanitsa G.D. Preprocessing of unstructured medical data: the impact of each preprocessing stage on classification//Procedia Computer Science, 2020, Vol. 178, pp. 284-290 | 2020 | Scopus, Web of Science |
| Kopanitsa G.D., Metsker O.G., Yakovlev A., Fedorenko A., Zvartau N.E. Modelling of COVID-19 morbidity in russia//Studies in health technology and informatics, 2020, Vol. 273, pp. 262-265 | 2020 | Scopus, Web of Science |
| Metsker O., Kopanitsa G.D., Komlichenko E., Yanushanets M., Bolgova E.V. Prediction of a due date based on the pregnancy history data using machine learning//Studies in health technology and informatics, 2020, Vol. 273, pp. 104-108 | 2020 | Scopus, Web of Science |
| Kopanitsa G.D. Follow-up on the abnormal laboratory test results with automatic interpretation//Studies in health technology and informatics, 2020, Vol. 273, pp. 240-245 | 2020 | Scopus, Web of Science |
| Behar J., Liu C., Kotzen K., Tsutsui K., Corino V.D., Singh J., Pimentel M.A., Warrick P., Zaunseder S., Andreotti F., Sebag D., Kopanitsa G., Mcsharry P.E., Karlen W., Karmakar C., Clifford G. Remote health diagnosis and monitoring in the time of COVID-19//Physiological Measurement, 2020, Vol. 41, No. 10, pp. 10TR01 | 2020 | Scopus, Web of Science |
| Metsker O., Kopanitsa G.D., Bolgova E.V. Prediction of childbirth mortality using machine learning//Studies in health technology and informatics, 2020, Vol. 273, pp. 109-114 | 2020 | Scopus, Web of Science |
| Metsker O., Magoev K., Yanishevskiy S., Yakovlev A., Kopanitsa G.D., Zvartau N.E. Identification of diabetes risk factors in chronic cardiovascular patients//Studies in health technology and informatics, 2020, Vol. 273, pp. 136-141 | 2020 | Scopus, Web of Science |
| Lenivtceva I.D., Kashina M., Kopanitsa G.D. Category of Allergy Identification from Free-Text Medical Records for Data Interoperability//Studies in health technology and informatics, 2020, Vol. 273, pp. 170-175 | 2020 | Scopus, Web of Science |
| Dudchenko A., Ganzinger M., Kopanitsa G.D. Machine learning algorithms in cardiology domain: A systematic review//Open Bioinformatics Journal, 2020, Vol. 13, No. 1, pp. 25-40 | 2020 | Scopus |
| 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 | 2020 | Scopus, Web of Science |
| Lenivtceva I.D., Slasten E.S., Kashina M., Kopanitsa G.D. Applicability of Machine Learning Methods to Multi-label Medical Text Classification//Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2020, Vol. 12140 LNCS, pp. 509-522 | 2020 | Scopus, Web of Science |
| Kopanitsa G.D. Automatic Interpretation of Laboratory Tests and Its Influence on Follow-up//Studies in health technology and informatics, 2020, Vol. 270, pp. 916-920 | 2020 | Scopus, Web of Science |
| Metsker O., Vozniuk I., Kopanitsa G.D., Morozova E., Prohorova M. Stroke ICU patient mortality day prediction//Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2020, Vol. 12140 LNCS, pp. 390-405 | 2020 | Scopus, Web of Science |
| Metsker O., Magoev K., Yanishevskiy S., Yakovlev A., Kopanitsa G.D. Risk Factors for Chronic Diabetes Patients//Studies in health technology and informatics, 2020, Vol. 270, pp. 1379-1380 | 2020 | Scopus, Web of Science |
| Semenov I., Osenev R., Gerasimov S., Kopanitsa G.D., Denisov D., Andreychuk Y. Experience in Developing an FHIR Medical Data Management Platform to Provide Clinical Decision Support//International Journal of Environmental Research and Public Health, 2020, Vol. 17, No. 1, pp. 73 | 2020 | Scopus, Web of Science |
| Metsker O., Efimov E., Trofimov E., Kopanitsa G.D., Bolgova E.V., Yakovlev A. Performance Improvement Algorithms in Big Data Analysis//Procedia Computer Science, 2020, Vol. 178, pp. 386-393 | 2020 | Scopus, Web of Science |
| Dudchenko A., Dudchenko P., Ganzinger M., Kopanitsa G.D. Extraction from Medical Records//Studies in health technology and informatics, 2019, Vol. 261, pp. 62-67 | 2019 | Scopus, Web of Science |
| Bobrova M., Taranik M.A., Kopanitsa G.D. Using Neural Networks for Diagnosing in Dermatology//Studies in health technology and informatics, 2019, Vol. 261, pp. 211-216 | 2019 | Scopus, Web of Science |
| Lenivtceva I.D., Kopanitsa G.D. Evaluating Manual Mappings of Russian Proprietary Formats and Terminologies to FHIR//Methods of Information in Medicine, 2019, Vol. 58, No. 4-5, pp. 151-159 | 2019 | Scopus, Web of Science |
| Dudchenko A., Ganzinger M., Kopanitsa G.D. Optimization of Clinical Decision Support Based on Pearson Correlation of Attributes//Studies in health technology and informatics, 2019, Vol. 261, pp. 199-204 | 2019 | Scopus, Web of Science |
| Dudchenko A., Kopanitsa G.D. Comparison of word embeddings for extraction from medical records//International Journal of Environmental Research and Public Health, 2019, Vol. 16, No. 22, pp. 4360 | 2019 | Scopus, Web of Science |
| Taranik M., Kopanitsa G.D. Using Machine Learning for Personalized Patient Adherence Level Determination//Studies in health technology and informatics, 2019, Vol. 261, pp. 174-178 | 2019 | Scopus, Web of Science |
| Dudchenko P., Dudchenko A., Kopanitsa G.D. Heart Disease Dataset Clusterization//Studies in health technology and informatics, 2019, Vol. 261, pp. 162-167 | 2019 | Scopus, Web of Science |
| Dudchenko A., Ganzinger M., Kopanitsa G.D. Diagnoses Detection in Short Snippets of Narrative Medical Texts//Procedia Computer Science, 2019, Vol. 156, pp. 150-157 | 2019 | Scopus, Web of Science |
| Kopanitsa G.D. Microservice Architecture to Provide Medical Data Management for Decision Support//Studies in health technology and informatics, 2019, Vol. 261, pp. 230-235 | 2019 | Scopus, Web of Science |
| Lenivtseva Y.D., Kopanitsa G.D. Investigation of Content Overlap in Proprietary Medical Mappings//Studies in health technology and informatics, 2019, Vol. 258, pp. 41-45 | 2019 | Scopus, Web of Science |
| Dudchenko A., Kopanitsa G.D., Knaup P., Ganzinger M. A Predictive Model for Patient Similarity: Classes Based on Secondary Data and Simple Measurements as Predictors//Studies in health technology and informatics, 2018, Vol. 249, pp. 167-172 | 2018 | Scopus, Web of Science |
| Dudchenko A., Kopanitsa G. Decision support systems in cardiology: A systematic review//Studies in health technology and informatics, 2017, Vol. 237, pp. 209-214 | 2017 | Scopus, Web of Science |