A5047596586- COVID-19 epidemiological studies
- Information Systems and Technology Applications
- Environmental and Biological Research in Conflict Zones
- Legal, Health, Environmental and COVID-19 Challenges
- Technology and Human Factors in Education and Health
- COVID-19 diagnosis using AI
- Advanced Data Processing Techniques
- Statistical and Computational Modeling
- Artificial Intelligence in Healthcare
- Business and Economic Development
- Diverse Scientific Research in Ukraine
- Misinformation and Its Impacts
- Artificial Intelligence in Healthcare and Education
- Mathematical and Theoretical Epidemiology and Ecology Models
- Heart Rate Variability and Autonomic Control
- Healthcare Systems and Public Health
- Data-Driven Disease Surveillance
- Network Security and Intrusion Detection
- Advanced Computational Techniques in Science and Engineering
- Migration, Health and Trauma
- Health and Conflict Studies
- Spam and Phishing Detection
- Cybersecurity and Information Systems
- Economic and Technological Systems Analysis
- Viral Infections and Vectors
National Aerospace University – Kharkiv Aviation Institute
2016-2025
University of Waterloo
2023-2025
Balsillie School of International Affairs
2025
Massachusetts Institute of Technology
2024
Technical University of Applied Sciences Wildau
2022-2023
C-Com Satellite Systems (Canada)
2021
Computer Algorithms for Medicine
2021
O.M. Beketov National University of Urban Economy in Kharkiv
2019
Abstract Despite notable scientific and medical advances, broader political, socioeconomic behavioural factors continue to undercut the response COVID-19 pandemic 1,2 . Here we convened, as part of this Delphi study, a diverse, multidisciplinary panel 386 academic, health, non-governmental organization, government other experts in from 112 countries territories recommend specific actions end persistent global threat public health. The developed set 41 consensus statements 57 recommendations...
Background We examined the human toll and subsequent humanitarian crisis resulting from Russian invasion of Ukraine, which began on 24 February 2022. Method extracted analysed data military attacks Ukrainians between 4 August The tracked direct deaths injuries, damage to healthcare infrastructure impact health, destruction residences, infrastructure, communication systems, utility services – all disrupted lives Ukrainians. Results As 2022, 5552 civilians were killed outright 8513 injured in...
Importance Since the full-scale Russian invasion, hospitals in Ukraine have been compelled to close or operate at reduced capacity due inadequate supplies, damage, destruction caused by war. Objective To analyze hospital services during period before and after invasion. Design, Setting, Participants Of 450 currently functioning Ukraine, a cross-sectional survey was carried out with participation of 74 from 12 oblasts. Hospital administrators responded an online questions on use services....
To identify the early predictors of a self-reported persistence long COVID syndrome (LCS) at 12 months after hospitalisation and to propose prognostic model its development. A combined cross-sectional prospective observational study. tertiary care hospital. 221 patients hospitalised for COVID-19 who have undergone comprehensive clinical, sonographic survey-based evaluation predischarge 1 month with subsequent 12-month follow-up. The final cohort included 166 had completed visit months. LCS...
The rapid dissemination of information has been accompanied by the proliferation fake news, posing significant challenges in discerning authentic news from fabricated narratives. This study addresses urgent need for effective detection mechanisms. spread on digital platforms necessitated development sophisticated tools accurate and classification. Deep learning models, particularly Bi-LSTM attention-based architectures, have shown promise tackling this issue. research utilized integrating an...
Integrating artificial intelligence (AI) into public health has emerged as a transformative force, reshaping how data are collected, analyzed, and utilized [...]
COVID-19 has become the largest pandemic in recent history to sweep world. This study is devoted developing and investigating three models of epidemic process based on statistical machine learning evaluation results their forecasting. The developed are Random Forest, K-Nearest Neighbors, Gradient Boosting methods. were studied for adequacy accuracy predictive incidence 3, 7, 10, 14, 21, 30 days. used data new cases Germany, Japan, South Korea, Ukraine. These countries selected because they...
Natural Language Processing (NLP) is a subset of artificial intelligence that enables machines to understand and respond human language through Large Models (LLMs)‥ These models have diverse applications in fields such as medical research, scientific writing, publishing, but concerns hallucination, ethical issues, bias, cybersecurity need be addressed. To the community’s understanding perspective on role Artificial Intelligence (AI) research authorship, survey was designed for corresponding...
Artificial intelligence (AI) chatbots have the potential to revolutionize online health information-seeking behavior by delivering up-to-date information on a wide range of topics. They generate personalized responses user queries through their ability process extensive amounts text, analyze trends, and natural language responses. Chatbots can manage infodemic debunking misinformation large scale. Nevertheless, system accuracy remains technically challenging. require training diverse...
For more than a month now, Russian troops have been destroying the Russian-speaking city of Kharkiv in Ukraine, where we live, along with 1.5 million other inhabitants.In Kharkiv, war has resulted deaths hundreds civilians, large-scale destruction infrastructure, and also humanitarian crisis, which is getting worse every day.There are estimates that 1,000 buildings destroyed, 700 multi-storey apartment buildings, no longer habitable.Essential infrastructure city, such as water supply,...
Human resource management during project implementation in a multi-project environment requires addressing the resource-constrained scheduling problem. Agile methodologies allow for greater flexibility, necessitating an agile transformation of human processes. Changes occurring lead to modifications initial team and alterations state pool environment. To ensure controllable changes address task allocating (reallocating) limited resources among tasks with subsequent optimization based on...
The research is devoted to the problem of predicting incidence gastroenterocollitis. paper discusses forecasting time series by statistical models. methods exponential smoothing and adaptive are proposed, applied additive multiplicative analysis results obtained using developed computer aided system.
The share of chronic odontogenic rhinosinusitis is 40% among all rhinosinusitis. Using automated information systems for differential diagnosis will improve the efficiency decision-making by doctors in diagnosing Therefore, this study aimed to develop an intelligent decision support system based on computer vision methods. A dataset was collected and processed, including 162 MSCT images. deep learning model image segmentation developed. 23 convolutional layer U-Net network architecture has...
This paper addresses the maximum coverage location problem in a generalized setting, where both facilities (service areas) and regional demand are modeled as continuous entities. Unlike traditional formulations, our approach allows for arbitrary shapes service areas regions, with additional constraints on facility placement. The key novelty of this work is its ability to handle complex, irregularly shaped areas, including approximating them unions centrally symmetric shapes. enables use an...
The paper analyzes existing approaches of mathematical modeling morbidity spreading by the example dynamics influenza and ARVI. analysis showed that most perspective approach is an agent-based. Agent-based model with SEIR type which takes into account behavior, age groups, as well special features ARVI has been developed. Software implementation allows forecasting morbidity, calculating epidemic threshold realized using C# programming language. relevance tested on real statistics.
In this paper the model and applied information system are proposed for modelling cash flow of insurance funds with use cloud data storage. Cash valuation is performed taking into account contextual characteristics an insured under conditions stochastic uncertainty. The financial fund company allow to solvency probability based on analysis properties insureds, that increase estimation accuracy modeling flows. Also, takes bonus non-payment during operation. paper, we propose a structure...
The problem of information protection in telecommunication networks related to the prevention epidemics malicious software is considered. An analysis deterministic models propagation computer viruses a heterogeneous network taking into account its topological and architectural features carried out. A class epidemic caused by worms highlighted. multi-agent model worm proposed adequacy shown on basis comparative study existing mathematical models. graphs dependence number infected nodes time...
Abstract The integration of radar technology into smart furniture represents a practical approach to health monitoring, circumventing the concerns regarding user convenience and privacy often encountered by conventional home systems. Radar technology’s inherent non-contact methodology, privacy-preserving features, adaptability diverse environmental conditions, high precision characteristics collectively establish it compelling alternative for comprehensive monitoring within domestic...
Topicality. Efficient multi-object control in network environments ensures optimal performance and reliability. Due to delays errors, traditional methods often face challenges managing complex, large-scale networks. The aim of the research. This study aims evaluate compare efficiency reliability three distinct methods: independent control, sequential with error correction, simultaneous global correction. Research methods. research employs mathematical modelling, probabilistic time graphs,...
The spread of health-related misinformation has become a significant global challenge, particularly during the COVID-19 pandemic. This study introduces comprehensive framework for detecting and analyzing using advanced natural language processing techniques. proposed classification model combines BERT embeddings with Bi-LSTM architecture attention mechanisms, achieving high performance, including 99.47% accuracy an F1-score 0.9947. In addition to classification, topic modeling is employed...