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ORCIDGeorgy D. Kopanitsa
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2020 – today
- 2022
[j8]Sergey V. Kovalchuk, Georgy D. Kopanitsa, Ilia V. Derevitskii
, Georgy A. Matveev, Daria A. Savitskaya:
Three-stage intelligent support of clinical decision making for higher trust, validity, and explainability. J. Biomed. Informatics 127: 104013 (2022)- [j7]Georgy D. Kopanitsa:
Study of patients' attitude to automatic interpretation of laboratory test results and its influence on follow-up rate. BMC Medical Informatics Decis. Mak. 22(1): 79 (2022) - [c59]Georgy D. Kopanitsa, Sergey V. Kovalchuk:
Study of the User Behaviour Caused by Automatic Recommendation Systems Call to Action. HEALTHINF 2022: 499-503 - [c58]Aleksandr Gerasimov, Egor Trofimov, Georgy D. Kopanitsa, Oleg G. Metsker:
Modelling Investment Programs with Machine Learning and Data Mining: Descriptive and Predictive Models of Healthcare State Programs in Russia. FRUCT 2022: 1-6 - [c57]Elizaveta Dubasova, Artem Berdashkevich, Georgy D. Kopanitsa, Pavel Kashlikov, Oleg G. Metsker:
Social Network Users Profiling Using Machine Learning for Information Security Tasks. FRUCT 2022: 87-92 - [c56]Georgy D. Kopanitsa, Sergey V. Kovalchuk:
Study of the User Behaviour Caused by Automatic Recommendation Systems Call to Action. pHealth 2022: 89-96 - 2021
- [c55]Georgy D. Kopanitsa, Ilia V. Derevitskii, Daria A. Savitskaya, Sergey V. Kovalchuk:
Assessing Acceptance Level of a Hybrid Clinical Decision Support Systems. EFMI-STC 2021: 18-22 - [c54]Oleg G. Metsker, Georgy D. Kopanitsa:
Influence of Healthcare Organization Factors on Cardiovascular Diseases Mortality. EFMI-STC 2021: 149-152 - [c53]David Paskoshev, Georgy D. Kopanitsa, Egor Trofimov, Oleg G. Metsker:
Simulation of a Judicial Process Using Machine Learning to Analyze Administrative Prejudice and Indicate the Quality of Justice. FRUCT 2021: 165-170 - [c52]Oleg G. Metsker, Egor Trofimov, Georgy D. Kopanitsa:
Application of Machine Learning Metrics for Dynamic E-justice Processes. FRUCT 2021: 293-300 - [c51]Oleg G. Metzker, Georgy D. Kopanitsa, Anton Malushko, Eduard Komlichenko, Katerina V. Bolgova, David Paskoshev:
Gynecological Surgery and Machine Learning: Complications and Length of Stay Prediction. MIE 2021: 575-579 - [c50]Iuliia Lenivtceva, Sofia Grechishcheva, Georgy D. Kopanitsa, Dmitry Panfilov, Boris N. Kozlov:
Predicting the Aortic Aneurysm Postoperative Risks Based on Russian Integrated Data. pHealth 2021: 88-93 - [c49]Oleg G. Metsker, Georgy D. Kopanitsa, Olga Irtyuga, Vladimir Uspenskiy:
Dynamic Aortic Aneurism Risk Factors. pHealth 2021: 130-135 - [c48]Georgy D. Kopanitsa, Oleg G. Metsker, Ekaterina V. Bolgova, Sergey V. Kovalchuk:
Lifestyle Cancer Survival Predictors: Influence of Vegetarian Diet on the Relapse of Endometrial Cancer. pHealth 2021: 193-198 - [c47]Egor Trofimov, Oleg G. Metsker, Georgy D. Kopanitsa, David Pashoshev:
Regulation Modelling and Analysis Using Machine Learning During the Covid-19 Pandemic in Russia. pHealth 2021: 259-264 - 2020
- [j6]Oleg G. Metsker, Kirill Magoev, Alexey N. Yakovlev, Stanislav Yanishevskiy, Georgy D. Kopanitsa, Sergey V. Kovalchuk, Valeria V. Krzhizhanovskaya:
Identification of risk factors for patients with diabetes: diabetic polyneuropathy case study. BMC Medical Informatics Decis. Mak. 20(1): 201 (2020) - [c46]Oleg G. Metsker, Vozniuk Igor, Georgy D. Kopanitsa, Elena Morozova, Prohorova Maria:
Stroke ICU Patient Mortality Day Prediction. ICCS (4) 2020: 390-405 - [c45]Iuliia Lenivtceva, Evgenia Slasten, Mariya Kashina, Georgy D. Kopanitsa:
Applicability of Machine Learning Methods to Multi-label Medical Text Classification. ICCS (4) 2020: 509-522 - [c44]Georgy D. Kopanitsa:
Automatic Interpretation of Laboratory Tests and Its Influence on Follow-up. MIE 2020: 916-920 - [c43]Oleg G. Metsker, Kirill Magoev, Stanislav Yanishevskiy, Alexey N. Yakovlev, Georgy D. Kopanitsa:
Risk Factors for Chronic Diabetes Patients. MIE 2020: 1379-1380 - [c42]Oleg G. Metsker, Georgy D. Kopanitsa, Eduard Komlichenko, Maria Yanushanets, Ekaterina V. Bolgova:
Prediction of a Due Date Based on the Pregnancy History Data Using Machine Learning. pHealth 2020: 104-108 - [c41]Oleg G. Metsker, Georgy D. Kopanitsa, Ekaterina V. Bolgova:
Prediction of Childbirth Mortality Using Machine Learning. pHealth 2020: 109-114 - [c40]Oleg G. Metsker, Kirill Magoev, Stanislav Yanishevskiy, Alexey N. Yakovlev, Georgy D. Kopanitsa, Nadezhda Zvartau:
Identification of Diabetes Risk Factors in Chronic Cardiovascular Patients. pHealth 2020: 136-141 - [c39]Iuliia Lenivtceva, Mariya Kashina, Georgy D. Kopanitsa:
Category of Allergy Identification from Free-Text Medical Records for Data Interoperability. pHealth 2020: 170-175 - [c38]Oleg G. Metsker, Georgy D. Kopanitsa, Alexey N. Yakovlev, Karlina Veronika, Nadezhda Zvartau:
Survival Analysis of COVID-19 Patients in Russia Using Machine Learning. pHealth 2020: 223-227 - [c37]Georgy D. Kopanitsa:
Follow-Up on the Abnormal Laboratory Test Results with Automatic Interpretation. pHealth 2020: 240-245 - [c36]Georgy D. Kopanitsa, Oleg G. Metsker, Alexey N. Yakovlev, Alexey Fedorenko, Nadezhda Zvartau:
Modelling of COVID-19 Morbidity in Russia. pHealth 2020: 262-265 - [i1]Sergey V. Kovalchuk, Georgy D. Kopanitsa, Ilya V. Derevitskii, Daria A. Savitskaya:
Three-stage intelligent support of clinical decision making for higher trust, validity, and explainability. CoRR abs/2007.12870 (2020)
2010 – 2019
- 2019
- [c35]Yulia Lenivtseva, Georgy D. Kopanitsa:
Investigation of Content Overlap in Proprietary Medical Mappings. EFMI-STC 2019: 41-45 - [c34]Aleksei Dudchenko, Polina Dudchenko, Matthias Ganzinger, Georgy D. Kopanitsa:
Extraction from Medical Records. pHealth 2019: 62-67 - [c33]Polina Dudchenko, Aleksei Dudchenko, Georgy D. Kopanitsa:
Heart Disease Dataset Clusterization. pHealth 2019: 162-167 - [c32]Maksim Taranik, Georgy D. Kopanitsa:
Using Machine Learning for Personalized Patient Adherence Level Determination. pHealth 2019: 174-178 - [c31]Aleksei Dudchenko, Matthias Ganzinger, Georgy D. Kopanitsa:
Optimization of Clinical Decision Support Based on Pearson Correlation of Attributes. pHealth 2019: 199-204 - [c30]Margarita Bobrova, Maksim Taranik, Georgy D. Kopanitsa:
Using Neural Networks for Diagnosing in Dermatology. pHealth 2019: 211-216 - [c29]Georgy D. Kopanitsa:
Microservice Architecture to Provide Medical Data Management for Decision Support. pHealth 2019: 230-235 - 2018
- [j5]Ilia Semenov, Georgy D. Kopanitsa, Dmitry Denisov, Yakovenko Alexandr, Roman Osenev, Yury Andreychuk:
Patients Decision Aid System Based on FHIR Profiles. J. Medical Syst. 42(9): 166:1-166:16 (2018) - [j4]Georgy D. Kopanitsa, Ilia Semenov:
Patient facing decision support system for interpretation of laboratory test results. BMC Medical Informatics Decis. Mak. 18(1): 68:1-68:13 (2018) - [c28]Svetlana Nikitina, Florian Daniel, Marcos Báez, Fabio Casati, Georgy D. Kopanitsa:
Crowdsourcing for Reminiscence Chatbot Design. HCOMP (WIP&Demo) 2018 - [c27]Georgy D. Kopanitsa, Alexandr Ivanov:
Implementation of Fast Healthcare Interoperability Resources for an Integration of Laboratory and Hospital Information Systems. MIE 2018: 11-15 - [c26]Ilia Semenov, Georgy D. Kopanitsa:
Decision Support System Based on FHIR Profiles. pHealth 2018: 117-121 - [c25]Aleksei Dudchenko, Georgy D. Kopanitsa, Petra Knaup, Matthias Ganzinger:
A Predictive Model for Patient Similarity: Classes Based on Secondary Data and Simple Measurements as Predictors. pHealth 2018: 167-172 - 2017
- [j3]Georgy D. Kopanitsa:
A Qualitative Study of the Barriers and Opportunities for Adoption of Web-Portals for Doctors and Patients in Russia. J. Medical Syst. 41(4): 62:1-62:7 (2017) - [c24]Georgy D. Kopanitsa, Zhanna Kopanitsa:
Implementation and Evaluation of a Decision Support Systems for the Patients of a Laboratory Service. ICIST 2017: 119-128 - [c23]Maksim Taranik, Georgy D. Kopanitsa:
Decision Support System for Medical Care Quality Assessment Based on Health Records Analysis in Russia. ICIST 2017: 203-209 - [c22]Georgy D. Kopanitsa:
Evaluation of a Decision Support System for Laboratory Service Patients. MedInfo 2017: 1063-1065 - [c21]Maksim Taranik, Georgy D. Kopanitsa:
Patient's Adherence Level Determination System. MedInfo 2017: 1306 - [c20]Georgy D. Kopanitsa:
Implementation of an Archetype Data Set to Reuse Electronic Health Record Data in Clinical Decision Support Systems. MedInfo 2017: 1329 - [c19]Maksim Taranik, Georgy D. Kopanitsa:
Decision Support System for Medical Care Quality Assessment Based on Health Records Analysis in Russia. MedInfo 2017: 1371 - [c18]Maksim Taranik, Georgy D. Kopanitsa:
Information System of Personalized Patient's Adherence Level Determination. pHealth 2017: 68-72 - [c17]Georgy D. Kopanitsa:
User Requirements Based Development of a Web Portal for Chronic Patients. pHealth 2017: 171-176 - [c16]Aleksey Dudchenko, Georgy D. Kopanitsa:
Decision Support Systems in Cardiology: A Systematic Review. pHealth 2017: 209-214 - 2016
- [c15]Ilya Semenov, Georgy D. Kopanitsa:
Development of a Clinical Decision Support System for the Patients of a Laboratory Service. MIE 2016: 90-94 - [c14]Georgy D. Kopanitsa, Anatoly Karpov, Georgy Lakovenko, Andrey Laskovenko, Vladimir Yampolsky:
Exploring Barriers and Opportunities for Adoption of Web Portals in Russia. Example of a Tuberculosis Portal. pHealth 2016: 170-174 - [c13]Ilya Semenov, Georgy D. Kopanitsa, Anatoly Karpov, Georgy Lakovenko, Andrey Laskovenko:
Implementation of a Clinical Decision Support System for Interpretation of Laboratory Tests for Patients. pHealth 2016: 184-188 - [c12]Georgy D. Kopanitsa, Anatoly Karpov, Georgy Lakovenko, Andrey Laskovenko:
Implementation of a Web Portal for Diabetes Patients Using Open Source Data Visualization Libraries. pHealth 2016: 189-194 - 2015
- [j2]Georgy D. Kopanitsa, Hasan Veseli, Vladimir Yampolsky:
Development, implementation and evaluation of an information model for archetype based user responsive medical data visualization. J. Biomed. Informatics 55: 196-205 (2015) - [j1]Georgy D. Kopanitsa:
Evaluation Study for an ISO 13606 Archetype Based Medical Data Visualization Method. J. Medical Syst. 39(8): 82 (2015) - [c11]Georgy D. Kopanitsa, Maxim Taranik:
Application of ISO 13606 Archetypes for an Integration of Hospital and Laboratory Information Systems. ICIST 2015: 29-36 - [c10]Georgy D. Kopanitsa, Maxim Taranik:
Using Semi-automated Approach for Mapping Local Russian Laboratory Terms to LOINC. ICIST 2015: 37-44 - [c9]Georgy D. Kopanitsa, Vladimir Yampolskiy:
Approach to Extract Billing Data from Medical Documentation in Russia - Lessons Learned. MIE 2015: 349-353 - [c8]Georgy D. Kopanitsa:
Mapping Russian Laboratory Terms to LOINC. MIE 2015: 379-383 - [c7]Georgy D. Kopanitsa, Vladimir Yampolsky:
Application of ISO 13606 Archetypes for a HIS-LIS integration. MIE 2015: 1018 - 2014
- [c6]Georgy D. Kopanitsa:
Application of UML Connectors for Arranging Medical Archetypes into a Knowledge Base. HEALTHINF 2014: 250-255 - [c5]Georgy D. Kopanitsa:
Arranging ISO 13606 Archetypes into a Knowledge Base. MIE 2014: 33-37 - 2013
- [c4]Georgy D. Kopanitsa, Claudia Hildebrand, Hans Demski:
Applying UML Connectors for Arranging Medical Archetypes into a Knowledge Base. MedInfo 2013: 1097 - 2012
- [c3]Georgy D. Kopanitsa, Zhanna Tsvetkova, Hasan Veseli:
Analysis of Metrics for the Usability Evaluation of Electronic Health Record Systems. EFMI-STC 2012: 129-133 - [c2]Georgy D. Kopanitsa:
Standard Based Multiclient Medical Data Visualization. MIE 2012: 199-203 - [c1]Georgy D. Kopanitsa, Zhanna Tsvetkova, Hasan Veseli:
Analysis of Metrics for the Usability Evaluation of EHR Management Systems. MIE 2012: 358-362
Coauthor Index
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