Andrii Sverstiuk

@tdmu.edu.ua

Andrii Sverstiuk


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https://researchid.co/sverstiuk
Andrii Sverstiuk received the master’s degree in applied math, the Ph.D. degree in systems analysis and decision making, and the D.Sc. degree in Mathematical modelling and computational methods making from the Taras Shevchenko National University of Kyiv and Ternopil National Technical University, Ukraine, in 2010 and 2020, respectively. Since 2002, he was working as a Assistance, Associate Professor and a Professor of the Medical Informatics Department of I. Horbachevsky Ternopil National Medical University, Ukraine. His research interests include Big Data, Machine Learning, Medical Informatics, Biosensors, Signal Processing, Dynamic Systems and Population Dynamics.

EDUCATION

2000: Master's degree (with honor) in Biomedical Apparatus and Systems (specialty ID 8.05070204), Biomedical Systems Department, Ternopil National Technical University.
97

Scopus Publications

1225

Scholar Citations

18

Scholar h-index

37

Scholar i10-index

Scopus Publications

  • Soil quality classification from chemical composition using machine learning methods with SHAP-based explanation
    Halyna Humeniuk, Dmytro Tymoshchuk, Andrii Sverstiuk
    Environmental Challenges, 2026
    : The article investigates the possibilities of predicting soil quality based on the main agrochemical indicators using machine learning methods. The experimental base consisted of 768 soil samples collected from the territory of the Rozsoshansk community and 192 additional samples from the neighboring territory of the Izyaslav community Khmelnytskyi region, Ukraine, in the autumn of 2022-2023 and spring of 2022-2023. We determined exchangeable acidity, organic carbon, ammonium and nitrate nitrogen, mobile phosphorus, exchangeable calcium, and potassium for each sample. Based on the analyzed indicators, a generalized approach to assessing fertility levels was offered, categorizing soil quality into three classes. Machine learning methods were used to predict soil quality: Gaussian NB, Multinomial NB, Logistic Regression, Ridge Classifier, SGDC, Random Forest, XGBoost, kNN, SVM, and MLP neural network. Random Forest, XGBoost, and MLP demonstrated the highest accuracy on the test dataset. When testing on an independent dataset of 192 new samples, the MLP model preserved the best balance of classification performance metrics. It achieved high G-Mean values of 0.894 for class 1, 0.915 for class 2, and 0.903 for class 3, indicating the model’s effectiveness in both detecting the target class and correctly identifying the remaining classes. In addition, the model demonstrated strong F1-score values of 0.884, 0.921, and 0.773 accordingly. The constructed ROC and Precision–Recall curves further confirmed the high generalization capability of the proposed model. To interpret the operation of the neural network, the SHAP method was applied. Global SHAP analysis identified available phosphorus, soil acidity, and organic carbon as the most influential input features. Local SHAP explanations for sample No. 162 demonstrated physically meaningful and consistent model responses. The conducted SHAP analysis of the MLP neural network made it possible to quantitatively assess the contribution of individual input parameters to the prediction outcomes, which significantly increased the interpretability of the model and the level of confidence in the obtained results. The approach proposed in this study not only improves the accuracy of soil quality classification but also provides an agrochemical interpretation of the results, thereby creating a basis for the development of rational, efficient, and precision land use systems relevant to agronomists, land managers, and farmers.
  • Assessment of the Quality of Predicting the Risk of Chronic Mesotympanitis Recurrence in Patients Who Have Undergone Tympanoplasty
    Maksym I. Herasymiuk, Andrii Stepanovich Sverstiuk, Yuri B. Palaniza
    Indian Journal of Otology, 2026
    Chronic suppurative otitis media is a chronic infection of the middle ear, characterized by perforation of the eardrum with constant or periodic discharge from the middle ear for more than 2 months. The aim of the work is to propose a new original approach to assessing the quality of a multivariate regression model for predicting the recurrence of chronic mesotympanitis in patients with different degrees of risk based on the calculation of operational characteristics, ROC analysis with the construction of the corresponding curves and evaluation of the area under them. Materials and methods 111 patients (65 women and 46 men) aged 18 to 80 years with a diagnosis of chronic mesotympanitis who underwent surgery on the affected ear (tympanoplasty) were examined. Results To build a regression model, 13 probable factors for the occurrence of chronic mesotympanitis were used. To determine the diagnostic value of the model, the sensitivity (Se), specificity (Sp), positive (PPV) and negative predictive value (NPV), likelihood ratio of positive (LR+) and negative test (LR-), prediction accuracy % of the proposed mathematical model were calculated. To determine the predictive value of the model, ROC analysis was performed with the acquisition of ROC curves. Conclusions The construction of a multivariate regression model allows predicting the long-term results of surgical treatment and predicting the possibility of chronic mesotympanitis recurrence with a high sensitivity (97.99%), specificity (97.32%) and accuracy (97.89%).
  • Soil quality assessment based on agrochemical indicators and optimized multiple linear regression
    Dmytro Tymoshchuk, Halyna Humeniuk, Andrii Stepanovich Sverstiuk, Mariana Prokopiak, Oksana Matsiuk
    Journal of Ecological Engineering, 2026
    Soil quality assessment is a key component of sustainable land use, agroecosystem monitoring, and the optimization of agrochemical management.The aim of this study is to evaluate the soil quality within the Rozsoshansk community of the Khmelnytskyi region using the soil quality index (SQI) and to develop a statistically sound predictive model based on agrochemical indicators.The analysis was conducted using a set of soil parameters, including pH, C org , 4Spearman correlation analysis was performed, followed by the construction of a multiple linear regression model (R 2 = 0.904, Adjusted R 2 = 0.900), an assessment of multicollinearity (VIF), and ANOVA.Based on the results of the regression model with seven predictors, together with ANOVA and VIF diagnostics, an optimized model with four predictors (pH, C org , 4 + 3 -, , Ca 2+ ) was developed.This refined model demonstrated strong explanatory power (R 2 = 0.856, Adjusted R 2 = 0.853) and low prediction error.Residual diagnostics indicated deviations from normality and heteroscedasticity; however, robust estimation methods (OLS-HC3 and RLM using HuberT) confirmed the stability of the coefficient estimates.The findings suggest that soil organic carbon, exchangeable calcium, acidity, and nitrate nitrogen are the key indicators of soil quality in the study area.Future work will focus on applying machine learning methods for soil classification, integrating Explainable AI techniques to enhance the interpretability of predictive models.
  • Mathematical Optimization of Communication Networks Merging
    Andrii Sverstiuk, Oleg Lyashuk, Taras Dubyniak, Stepan Dubyniak, Oleksandra Manziy, Stanislav Andreychuk
    Lecture Notes in Intelligent Transportation and Infrastructure, 2026
  • Disadvantages in the professional activities of anesthesiologists and intensive care physicians: contemporary review of forensic-medical and legal practice
    V.V. Franchuk, P.R. Selskyy, A.S. Sverstiuk, V.V. Hnativ, O.Ye. Kuziv, M.V. Franchuk, A.F. Slyva
    Emergency Medicine Ukraine, 2026
    Background. Currently, clinical and expert characteristics, legal consequences of inadequate medical care in anesthesio­logy and intensive care in Ukraine have been studied insufficiently. Objective: to analyze court decisions and conclusions of forensic medical examinations in criminal proceedings initiated in Ukraine in recent years against anesthesiologists and intensive care physicians for professional negligence. Materials and methods. Official statistical data from the Unified State Register of Court Decisions for 2018–2024 were analyzed in cases concerning improper professional activity of healthcare workers. In addition, 123 reports of forensic medical examination regarding the prosecution of anesthesiologists from various regions of Ukraine from 2007 to 2024 were reviewed. Statistical processing was performed using multivariate regression analysis. Results. Ukrainian courts proved the guilt of anesthesiologists and intensive care physicians in the professional negligence in 81.2 % of legal proceedings against these doctors. According to forensic medical conclusions, different lacks of health care provision were identified in 71.5 % of the cases examined. Professional errors were most often committed in severe clinical situations related to respiratory or cardiovascular pathology, as well as trauma. The main types of errors included diagnostic (32.0 %), low quality medical treatment (26.0 %), institutional (14.0 %) and ethical (6.0 %) mistakes. Errors in medical records were detected in 22.0 % of the cases. Inadequate medical care in anesthesiology was predominantly insufficient (49.0 %) or delayed (37.0 %). Diagnostic errors most frequently occurred during associated management of patients with therapists and resulted in failur6e to provide timely care. Tactical errors were one of the main causes leading to criminal liability. The study proposes to distinguish the following categories of errors in anesthesiology and resuscitation: technical defects in the performance of anesthesia, preoperative, medication, perioperative, and postoperative errors. Conclusions. Anesthesiologists and intensive care physicians belong to the group of medical professionals with the highest risk of criminal prosecution. Diagnostic errors and improper performance of medical procedures or medication errors seemed to be most frequent in malpractice cases against anesthe­siologists. Increasing clinicians’ awareness of the types, causes, and consequences of medical errors is crucial for preventing adverse outcomes of medical practice.
  • Analysis of risk prediction models for neurological and musculoskeletal disorders in relation to quality-of-life indicators in post-stroke patients
    Natalia Shalabai, Svitlana Shkrobot, Dmytro Kovalchuk, Lyudmyla Mazur, Andrii Sverstiuk, Olena Hladii, Mariia Kulitska, Khrystyna Duve, Yaroslav Panasiuk
    Family Medicine and Primary Care Review, 2026
    Background.This study examined factors associated with quality of life in stroke patients as an important outcome measure after stroke that can contribute to a broader description of the disease and its consequences.Objectives.To provide a comparative analysis of risk prediction models for neurological and musculoskeletal disorders in relation to quality-of-life indicators in post-stroke patients.Material and methods.The study included 105 post-stroke patients with various symptoms of neurological and musculoskeletal disorders.The paper proposes risk criteria for neurological and musculoskeletal disorders, as well as quality-of-lifeindicators.Results.The prognostic model with quality-of-life indicators included such factors with a significance level of < 0.05 as social functioning, physical functioning, localization of lesion in the occipital region, symptoms of musculoskeletal disorders, dizziness, limb numbness, paresis, hemihypesthesia, and motor disorders.Conclusions.The proposed prognostic models are effective for the timely determination of RPN&MSD and RPN&MSDQoL while monitoring post-stroke patients and preventing complications.However, the RPN&MSDQoL model is more complete, as it includes the quality-of-life indicators PF and SF as important parameters for ensuring the effectiveness of comprehensive rehabilitation measures for post-stroke patients and has a higher determination coefficient R2 of 0.85 compared to 0.84 for the RPN&MSD model.
  • QUALITY OF LIFE IN CHILDREN WITH CHRONIC FATIGUE AND STRESS-RELATED DISORDERS: A SYSTEMATIC LITERATURE REVIEW
    S. Nikytiuk, S. Levenets, T. Hariyan, T. Hariyan, V. Synytska, A. Sverstiuk
    Neonatology Surgery and Perinatal Medicine, 2025
    To analyze data from contemporary scientific literature on the quality of life of children with chronic fatigue and stress-related disorders; to identify the the principal factors influencing their physical, emotional, and social functioning.Materials and methods. A systematic review of publications indexed in the PubMed, Scopus, Web of Science, and MEDLINE databases over the preceding 5–10 years was conducted. Studies that evaluated symptoms of chronic fatigue, stress-related disorders, and quality-of-life indicators in children and adolescents in the context of war were included in the analysis.Results and discussion Children with chronic fatigue and stress-related disorders associated with war exhibited reduced physical activity, as well as diminished emotional resilience, academic motivation, and social interaction. The most frequently identified factors contributing to diminished quality of life comprised prolonged stress, acute respiratory infections, sleep disturbances, difficulties with concentration, and recurrent somatic complaints. The importance of early diagnosis and the provision of comprehensive psychological and medical support was emphasised in the reviewed studies.Conclusions. Chronic fatigue and stress-related disorders substantially impair the quality of life of children, adversely affecting their physical, emotional, and social development. Chronic fatigue and stress-related disorders substantially impair the quality of life of children, adversely affecting their physical, emotional, and social development. The accumulated evidence underscores the requirement for integrated interventions incorporating medical, psychological, and social support, together with the development of effective assistance programmes for affected children and adolescents.
  • Local treatment of surgical wounds in patients with acute paraproctitis
    I. M. Shevchuk, O. V. Novitsky, R. T. Kuzenko, A. L. Shapoval, S. S. Snizhko, A. S. Sverstyuk
    Ukrainian Journal of Clinical Surgery, 2025
    Objective. To evaluate the effectiveness of sequential application of Acerbin solution and ointment (Austria) for local treatment of surgical wounds in patients with acute paraproctitis.Materials and methods. For the local treatment of surgical wounds in 57 patients with acute paraproctitis, Acerbin solution and ointment (Austria) were used, which have antiseptic, analgesic, anti-edema, and wound-healing effects.Results. Under the influence of the proposed treatment method, local pain syndrome disappeared on average in (7.02 ± 0.40) days, wound cleansing due to the transformation of wound exudates occurred on average in (7.11 ± 0.16) days, and granulation in the visible part of the wound appeared on average (7.72 ± 0.10) days after the operation (p&lt; 0.05). On the 8th day, only isolated colonies of microorganisms were cultured in patients treated with Acerbin solution and ointment. In patients treated without Acerbin solution and ointment, an average of (2.1 ± 0.4) × 105colony-forming units/cm3were isolated.Conclusions. Consistent use of Acerbin solution and ointment in patients with acute paraproctitis statistically significantly accelerated the elimination of perifocal tissue infiltration, cleansing of the wound from purulent-necrotic masses with the transformation of wound secretions, the appearance of granulations, and marginal epithelialization.
  • A Predictive Model for the Development of Long COVID in Children
    Vita Perestiuk, Andriy Sverstyuk, Tetyana Kosovska, Liubov Volianska, Oksana Boyarchuk
    International Journal of Environmental Research and Public Health, 2025
    Background/Objectives: Machine learning is an extremely important issue, considering the potential to prevent the onset of long-term complications from coronavirus disease or to ensure timely detection and effective treatment. The aim of our study was to develop an algorithm and mathematical model to predict the risk of developing long COVID in children who have had acute SARS-CoV-2 viral infection, taking into account a wide range of demographic, clinical, and laboratory parameters. Methods: We conducted a cross-sectional study involving 305 pediatric patients aged from 1 month to 18 years who had recovered from acute SARS-CoV-2 infection. To perform a detailed analysis of the factors influencing the development of long-term consequences of coronavirus disease in children, two models were created. The first model included basic demographic and clinical characteristics of the acute SARS-CoV-2 infection, as well as serum levels of vitamin D and zinc for all patients from both groups. The second model, in addition to the aforementioned parameters, also incorporated laboratory test results and included only hospitalized patients. Results: Among 265 children, 138 patients (52.0%) developed long COVID, and the remaining 127 (48.0%) fully recovered. We included 36 risk factors of developing long COVID in children (DLCC) in model 1, including non-hospitalized patients, and 58 predictors in model 2, excluding them. These included demographic characteristics of the children, major comorbid conditions, main symptoms and course of acute SARS-CoV-2 infection, and main parameters of complete blood count and coagulation profile. In the first model, which accounted for non-hospitalized patients, multivariate regression analysis identified obesity, a history of allergic disorders, and serum vitamin D deficiency as significant predictors of long COVID development. In the second model, limited to hospitalized patients, significant risk factors for long-term sequelae of acute SARS-CoV-2 infection included fever and the presence of ≥3 symptoms during the acute phase, a history of allergic conditions, thrombocytosis, neutrophilia, and altered prothrombin time, as determined by multivariate regression analysis. To assess the acceptability of the model as a whole, an ANOVA analysis was performed. Based on this method, it can be concluded that the model for predicting the risk of developing long COVID in children is highly acceptable, since the significance level is p &lt; 0.001, and the model itself will perform better than a simple prediction using average values. Conclusions: The results of multivariate regression analysis demonstrated that the presence of a burdened comorbid background—specifically obesity and allergic pathology—fever during the acute phase of the disease or the presence of three or more symptoms, as well as laboratory abnormalities including thrombocytosis, neutrophilia, alterations in prothrombin time (either shortened or prolonged), and reduced serum vitamin D levels, are predictors of long COVID development among pediatric patients.
  • PROGNOSIS FOR ENDOMETRIAL HYPERPLASIA PROGRESSION IN PREMENOPAUSAL AND MENOPAUSAL WOMEN BASED ON THE ANALYSIS OF CELLULAR IMMUNITY INDICATORS USING MULTIPARAMETRIC NEURAL NETWORK CLUSTERING
    Petro Selskyy, Olena Hladii, Svitlana Heryak, Andrii Sverstiuk, Andrii Slyva, Anatolii Televiak, Iryna Parahnyuk, Tetyana Golovata, Yurii Orel, Tetiana Adam
    Eastern Ukrainian Medical Journal, 2025
    Many factors play a role in the progression of endometrial hyperplasia and the increased risk of malignant transformation. One of the important factors influencing pathological tissue remodeling is the immune response. However, changes in cellular immunity have not yet been systematized into specific patterns of immunological response in hyperplasia. Therefore, the implementation of easy-to-use and relatively inexpensive information technologies and risk factor analysis techniques is particularly important. The objective of the study was to develop methods for predicting endometrial hyperplasia progression based on the analysis of morphological markers and indicators of cellular immunity using multiparametric neural network clustering. Materials and Methods. The indicators of the cellular component of general immunity were determined in 43 pre- and menopausal women, of whom 31 patients were diagnosed with endometrial hyperplasia without atypia, and 12 women were otherwise healthy and formed the control group. For deeper analysis, we applied an approach based on multiparameter neural network clustering using NeuroXL Classifier for Microsoft Excel. Results. In patients with endometrial hyperplasia, suppression of cellular immunity with a significant decrease in the percentage of all lymphocyte subpopulations was detected, whereas no significant changes in the immunoregulatory index were observed. It can indicate sufficient compensatory capabilities of the immune defense. The results of cluster analysis showed that in order to predict the progression of endometrial hyperplasia based on the analysis of the cellular immunity, it is important to consider the combination of reduced levels of CD3+ T-lymphocytes, CD4+ T-lymphocytes, and CD8+ T-lymphocytes, and increased levels of CD3+CD56+ NKT-like cells and CD56+ NK cells. Conclusions. Neural network clustering was used to objectively classify patients into risk groups for progression of endometrial hyperplasia based on the results of clustering the studied indicators, which allows determining the significance of combined changes in certain parameters for disease progression prognosis.
  • Optimization of scientific research of theoretical and methodological foundations of the formation of a culture of personal health
    , A.S. Sverstyuk, O.A. Bahrii-Zayats, , S.O. Nykytyuk, , S.S. Levenets, , T.V. Hariyan, , V.H. Dzhyvak, and
    Modern Pediatrics Ukraine, 2025
  • The Etiology and Epidemiology of Lyme Borreliosis
    Lyme Borreliosis, 2025
  • Preface
    Ceur Workshop Proceedings, 2025
  • Prediction Factors for Quality Risks in the Pharmaceutical Development of Tablets Bisoprolol Fumarate with Indapamide
    Nadia Malanchuk, Mariana Demchuk, Andriy Sverstiuk, Yuri Palaniza
    Adolescent Psychiatry, 2025
  • Using roc-analysis as a method of assessing the quality of prediction of the risk of progressing chronic tonsillitis
    Maksym Herasymiuk, Andrii Sverstiuk, Yuri Palaniza, Iryna Malovana
    Wiadomosci Lekarskie Warsaw Poland 1960, 2025
  • Increase the reliability of the device when duplicating the functions of individual nodes*
    Ceur Workshop Proceedings, 2025
  • Component method for analyzing the energy consumption signal as a periodically correlated random process
    Ceur Workshop Proceedings, 2025
  • Machine learning-based information technology for analyzing energy peaks in power grid balancing
    Ceur Workshop Proceedings, 2025
  • Antibacterial therapy for Lyme disease in children
    S.O. Nykytyuk, S.S. Levenets, T.V. Hariyan, I.P. Mironets, A.S. Sverstiuk
    Child S Health, 2025
  • An explainable artificial intelligence approach for detecting network attacks
    Ceur Workshop Proceedings, 2025
  • AutoML-Driven ECG Classification of Cardiac Pathologies with Explainable AI
    Ceur Workshop Proceedings, 2025
  • Approaches to the development of information technology for ECG analysis to evaluate quality of life in smart cities
    Ceur Workshop Proceedings, 2025
  • Optimizing form of a piezoelectric transformer*
    Ceur Workshop Proceedings, 2025
  • AutoML PyCaret and SHAP explainable AI for ECG signal classification based on amplitude variability
    Ceur Workshop Proceedings, 2025
  • Method and algorithm for wavelet detection of fetal ECG signal in the womb
    Ceur Workshop Proceedings, 2025
  • Vascular malformations in children: a rare case of vascular nevus and its clinical features
    , M.D. Protsailo, Yu.M. Orel, , S.V. Trach-Rosolovska, , S.O. Nykytuk, , A.Z. Mykolenko, , Z.O. Antyuk, , A.S. Sverstyuk, , V.H. Dzhyvak, and
    Modern Pediatrics Ukraine, 2025
  • Amperometric Biosensor Based on a Semipermeable Poly-Meta-Phenylenediamine Membrane and Immobilized Lactate Oxidase for Highly Accurate l-Lactate Determination in Blood Serum
    Kseniia Berketa, Anhelina Buzhak, Yevhen Vakhovskyi, Daryna Mruga, Andrii Sverstiuk, Olha Soldatkina, Olha Lyubovych, Olga Marchuk, Serhii Dzyadevych, Oleksandr Soldatkin
    Electroanalysis, 2025
  • Analytical review of the literature sources of the Scopus scientometric database on the prevention and prognosis of musculoskeletal disorders
    D.O. Kovalchuk, A.S. Sverstiuk, L.P. Mazur
    Ukraine Nation S Health, 2024
  • OPTIMIZATION OF THE SCIENTIFIC SEARCH FOR LYME BORRELIOSIS SEVERITY DIAGNOSTICS
    Andrii Sverstiuk, Svitlana Nykytyuk, Vira Synytska, Zhanna Antiuk, Olexandra Kyrychok
    Eastern Ukrainian Medical Journal, 2024
  • Amperometric Biosensor Based on Glutamate Oxidase to Determine Ast Activity
    Daryna Mruga, Kseniia Berketa, Andrii Sverstiuk, Vasyl Martsenyuk, Aleksandra Klos-Witkowska, Yurii Palianytsia, Sergei Dzyadevych, Oleksandr Soldatkin
    Sensors, 2024
  • PROGNOSIS OF LIMB MUSCULAR STRUCTURAL DISORDERS AFTER TOURNIQUET APPLICATION BASED ON THE CHANGES IN LIPID PEROXIDATION INDICATORS USING NEURAL NETWORK CLUSTERING
    Petro Selskyy, Anatolii Televiak, Vitalii Lutsyk, Valentyn Franchuk, Andriy Sverstiuk, Volodymyr Voloshyn, Mykhailo Furdela
    Eastern Ukrainian Medical Journal, 2024
  • Adaptation of Conductometric Monoenzyme Biosensor for Rapid Quantitative Analysis of L-arginine in Dietary Supplements
    Olga Y. Saiapina, Kseniia Berketa, Andrii S. Sverstiuk, Lyubov Fayura, Andriy A. Sibirny, Sergei Dzyadevych, Oleksandr O. Soldatkin
    Sensors, 2024
  • Preface
    Ceur Workshop Proceedings, 2024
  • Factors for evaluating the progress of chronic tonsillitis based on multifactor regression analysis
    Romanian Journal of Diabetes Nutrition and Metabolic Diseases, 2024
  • A MULTIFACTOR MODEL FOR ESTIMATING THE SENSITIVITY OF A HUMAN VESTIBULAR ANALYZER
    Horbachevsky Ternopil National Medical University, Ternopil, Ukraine, S.N. Vadzyuk, R.M. Shmata, Horbachevsky Ternopil National Medical University, Ternopil, Ukraine, A.S. Sverstyuk, Horbachevsky Ternopil National Medical University, Ternopil, Ukraine, T.A. Lebedeva, Horbachevsky Ternopil National Medical University, Ternopil, Ukraine
    Fiziologichnyi Zhurnal, 2024
  • Application of roc-analysis to assess the quality of predicting the risk of chronic rhinosinusitis recurrence
    Maksym Herasymiuk, Andrii Sverstiuk, Yuri Palaniza, Iryna Malovana
    Wiadomosci Lekarskie Warsaw Poland 1960, 2024
  • Analytical analysis of approaches to assessing the quality of life in smart cities
    Ceur Workshop Proceedings, 2024
  • Structure and Regularities of Development Information and Intellectual Capital Taking Into Account Acceleration of Digital Transformations in Conditions Information Society
    Ceur Workshop Proceedings, 2024
  • Estimation of accuracy, stiffness and stability of shell structures of mirror antennas using computer simulation
    Ceur Workshop Proceedings, 2024
  • Determination of heterogeneity of composite materials of shell structures by conductometric method
    Ceur Workshop Proceedings, 2024
  • Operational stability study of lactate biosensors: modeling, parameter identification, and stability analysis
    Vasyl Martsenyuk, Oleksandr Soldatkin, Aleksandra Klos-Witkowska, Andriy Sverstiuk, Ksenya Berketa
    Frontiers in Bioengineering and Biotechnology, 2024
  • Mathematical and computer modelling to assess accuracy and adequacy in torque measurement
    Ceur Workshop Proceedings, 2024
  • Analysis of the accuracy, stiffness and stability of shell structures of mirror antennas using computer modelling
    Ceur Workshop Proceedings, 2024
  • Study of the temperature effect on the functioning of photodetecting lighting elements and calculation of their reliability
    Ceur Workshop Proceedings, 2024
  • Statistically verified methods for determining predictors of development of arterial hypertension depending on endothelial nitric oxide synthase T786C gene promoter polymorphism using lipid profile indicators
    Svitlana Pidruchna, Volodimir Shmanko, Roman Hnizdyukh, Andrii Sverstiuk, Petro Lykhatskyy, Iryna Kuzmak, Tetyana Yaroshenko, Iryna Bandas, Nadya Vasylyshyn, Oksana Ostrivka, Alla Mudra, Lylya Palytsia, Nataliya Letnyak, Oleksandr Tokarskyy
    Endocrine Regulations, 2024
  • THE EFFECT OF PROBIOTIC THERAPY ON THE VAGINA MICROBIOTA AND THE HUMORAL LINK OF IMMUNITY IN BACTERIAL VAGINOSIS
    H.I. Mykhailyshyn, S.I. Klumnyuk, M.Ya. Spivak, A.S. Sverstiuk, L.M. Lazarenko
    Mikrobiolohichnyi Zhurnal, 2023
  • Evaluation of the effectiveness of rehabilitation for diabetic foot syndrome
    T. H. Bakaliuk, N. R. Маkarchuk, Kh. M. Seniuk, H. O. Stelmakh, A. S. Sverstiuk
    Zaporozhye Medical Journal, 2023
  • Prediction of the progression of endometrial hyperplasia in women of premenopausal and menopausal age based on an analysis of clinical and anamnestic indicators using multiparametric neural network clustering
    Petro Selskyy, Andrii Sverstiuk, Andrii Slyva, Boryslav Selskyi
    Family Medicine and Primary Care Review, 2023
  • Preface
    Ceur Workshop Proceedings, 2023
  • MULTIFACTOR REGRESSION MODEL FOR PREDICTION OF CHRONIC RHINOSINUSITIS RECURRENCE
    Maksym Herasymiuk, Andrii Sverstiuk, Iryna Kit
    Wiadomosci Lekarskie Warsaw Poland 1960, 2023
  • A multifactorial model for predicting severe course and organ and systems damage in Lyme borreliosis in children
    I.Ya. Horbachevsky Ternopil National Medical University, Ukraine, S.O. Nykytyuk, A.S. Sverstiuk, I.Ya. Horbachevsky Ternopil National Medical University, Ukraine, D.S. Pyvovarchuk, I.Ya. Horbachevsky Ternopil National Medical University, Ukraine, S.I. Klymnyuk, I.Ya. Horbachevsky Ternopil National Medical University, Ukraine
    Modern Pediatrics Ukraine, 2023
  • Rare forms of eye lesions in Lyme disease in children
    I.Y. Horbachevsky Ternopil National Medical University, Ukraine, S.O. Nykytyuk, T.V. Hariyan, I.Y. Horbachevsky Ternopil National Medical University, Ukraine, S.S. Levenets, I.Y. Horbachevsky Ternopil National Medical University, Ukraine, A.S. Sverstiuk, I.Y. Horbachevsky Ternopil National Medical University, Ukraine
    Modern Pediatrics Ukraine, 2023
  • Analysis of Lyme borreliosis incidence during the COVID-19 epidemic
    I. Horbachevsky Ternopil National Medical University, Ukraine, A.S. Sverstyuk, S.O. Nykytyuk, I. Horbachevsky Ternopil National Medical University, Ukraine, V.O. Panуchev, SI «Ternopil Regional Center for Disease Control, Prevention of the Ministry of Health of Ukraine», S.I. Klymnyuk, I. Horbachevsky Ternopil National Medical University, Ukraine, Y.B. Yakymchuk, I. Horbachevsky Ternopil National Medical University, Ukraine
    Modern Pediatrics Ukraine, 2023
  • Development of Model Predictive Control Algorithm for Managing Deformation of Multilayered Soil Massif under Mass and Heat Transfer
    Ceur Workshop Proceedings, 2023
  • Mathematical and Computer Simulation of the Response of a Potentiometric Biosensor for the Determination of α-сhaconine
    Ceur Workshop Proceedings, 2023
  • Approach to prediction and receiver operating characteristic analysis of a regression model for assessing the severity of the course Lyme borreliosis in children
    Svetlana oleksiivna Nykytyuk, Andriy Stepanovych Sverstiuk, Serhiy Ivanovich Klymnyuk, Dmytro Stepanovych Pyvovarchuk, Yuri Bogdanovich Palaniza
    Reumatologia, 2023
  • Bayesian click model and methods of estimating its parameters
    Ceur Workshop Proceedings, 2023
  • Multiparametric neural network clustering in prediction the risk of surgical complications after revascularization on great arteries of the lower extremities
    Ceur Workshop Proceedings, 2023
  • Human umbilical cord-derived мesenchymal stromal cells mitigate lipopolysaccharide-induced liver injury in rats
    I. Horbachevsky Ternopil National Medical University, O Redko, A. Dovgalyuk, I. Horbachevsky Ternopil National Medical University, Z. Nebesna, I. Horbachevsky Ternopil National Medical University, S. Kramar, I. Horbachevsky Ternopil National Medical University, A. Sverstyuk, I. Horbachevsky Ternopil National Medical University, M. Korda, I. Horbachevsky Ternopil National Medical University
    Cell and Organ Transplantology, 2023
  • EVALUATION OF POSTURAL BALANCE INDICATORS IN HEALTHY INDIVIDUALS
    Olha Farion-Navolska, Igor R. Mysula, Olha V. Denefil, Yuriy V. Zavidnyuk, Andriy Sverstyuk, Natalya Sydliaruk
    Wiadomosci Lekarskie Warsaw Poland 1960, 2023
  • MULTIFACTORIAL REGRESSION MODEL FOR PREDICTING THE LEVEL OF HEAT SENSITIVITY IN HEALTHY YOUNG PEOPLE IN THE CONTEXT OF GLOBAL WARMING
    Stepan N. Vadzyuk, Viktoria O. Huk, Tetiana V. Dzhyvak, Andriy S. Sverstiuk, Volodymyr H. Dzhyvak, Valentyna I. Bondarchuk, Uliana P. Hevko, Iryna M. Nikitina, Nadiіa V. Herevych
    Wiadomosci Lekarskie Warsaw Poland 1960, 2023
  • Prediction factors for the risk of diffuse non-toxic goiter development in type 2 diabetic patients
    Polski Merkuriusz Lekarski, 2022
  • Nonlinear Analytics for Electrochemical Biosensor Design Using Enzyme Aggregates and Delayed Mass Action
    Vasyl Martsenyuk, Aleksandra Klos-Witkowska, Sergei Dzyadevych, Andriy Sverstiuk
    Sensors, 2022
  • Prediction of climacteric syndrome development in perimenopausal women with hypothyroidism
    Oksana Chukur, Nadiya Pasyechko, Anzhela Bob, Andrii Sverstiuk
    Przeglad Menopauzalny, 2022
  • Qualitative and Quantitative Comparative Analysis of Results of Numerical Simulation of Cyber-Physical Biosensor Systems
    Ceur Workshop Proceedings, 2022
  • Quantitative analysis of fatty acids and monosaccharides composition in Chamerion angustifolium L. by GC/MS method
    Liudmyla Slobodianiuk, Liliia Budniak, Halyna Feshchenko, Andriy Sverstiuk, Yuri Palaniza
    Pharmacia, 2022
  • Analysis and Prediction of Humus Balance in Soils of Ukraine Using Informational Tools
    Ceur Workshop Proceedings, 2022
  • Study of the dissolution kinetics of drugs in solid dosage form with lisinopril and atorvastatin and intestinal permeability to assess their equivalence in vitro
    Nataliia Shulyak, Kateryna Liushuk, Oksana Semeniuk, Nadiya Yarema, Tetyana Uglyar, Dariya Popovych, Andriy Sverstiuk, Roman Ciciura, Liliya Logoyda
    Pharmacia, 2022
  • PREDICTION FACTORS FOR THE RISK OF HYPOTHYROIDISM DEVELOPMENT IN TYPE 2 DIABETIC PATIENTS
    Pharmacologyonline, 2021
  • Neural network clustering technology for cartographic images recognition
    Viktor Zhukovskyy, Serhii Shatnyi, Nataliia Zhukovska, Andriy Sverstiuk
    Eurocon 2021 19th IEEE International Conference on Smart Technologies Proceedings, 2021
  • Transformation of intellectual capital into intellectual-information in the process of formation and implementation modern information
    Ceur Workshop Proceedings, 2021
  • Predicting the risk of severe menopausal syndrome in perimenopausal women with hypothyroidism
    N.V. Pasechko, O.O. Chukur, A.O. Bob, A.S. Sverstiuk
    Miznarodnij Endokrinologicnij Zurnal, 2021
  • On Qualitative Research of Lattice Dynamical System of Two- and Three-Dimensional Biopixels Array
    Vasyl Martsenyuk, Mikolaj Karpinski, Aleksandra Klos-Witkowska, Andriy Sverstiuk
    Springer Proceedings in Mathematics and Statistics, 2021
  • Software for statistical processing and modeling of a set of synchronously registered cardio signals of different physical nature
    Ceur Workshop Proceedings, 2021
  • Methods of rhythm-cardio signals processing based on a mathematical model in the form of a vector of stationary and stationary connected random sequences
    Ceur Workshop Proceedings, 2021
  • Same bit-size moduli formation of residue number system for application in asymmetric cryptography
    Ceur Workshop Proceedings, 2021
  • Intelligent big data system based on scientific machine learning of cyber-physical systems of medical and biological processes
    Ceur Workshop Proceedings, 2021
  • Development and validation of spectrophotometric method for simultaneous estimation of valsartan and atenolol in binary mixtures: Aplication to tablets analysis
    Pharmakeftiki, 2021
  • Lc-ms/ms method development for the quantitative determination of valsartan from caco-2 cell monolayers: Application to permeability assay
    Pharmakeftiki, 2021
  • Statistical Simulation of the External Influence of the Information Spreading of the Population Models
    Oleksandr Nakonechnyi, Anatoliy Pashko, Andriy Sverstuik, Iuliia Shevchuk
    2020 IEEE 2nd International Conference on System Analysis and Intelligent Computing Saic 2020, 2020
  • Stability Investigation of Biosensor Model Based on Finite Lattice Difference Equations
    Vasyl Martsenyuk, Aleksandra Klos-Witkowska, Andriy Sverstiuk
    Springer Proceedings in Mathematics and Statistics, 2020
  • On Application of Kertesz Method for Exponential Estimation of Neural Network Model with Discrete Delays
    O. Nakonechnyi, V. Martsenyuk, A. Sverstiuk
    Mechanisms and Machine Science, 2020
  • Investigation of the mathematical model of the biosensor for the measurement of α-chaconine based on the impulsive differential system
    Ceur Workshop Proceedings, 2020
  • Software complex in the study of the mathematical model of cyber-physical systems
    Ceur Workshop Proceedings, 2020
  • Network modeling of coexistence of virus strains admitting chaotic behavior
    Ceur Workshop Proceedings, 2020
  • Youden’s test of the chromatographic determination of bisoprolol in dosage forms
    Pharmakeftiki, 2020
  • Vector of diagnostic features in the form of decomposition coefficients of statistical estimates using a cyclic random process model of cardiosignal
    Vasyl Martsenyuk, Andriy Sverstiuk, Aleksandra Klos-Witkowska, Andriy Horkunenko, Stanislaw Rajba
    Proceedings of the 2019 10th IEEE International Conference on Intelligent Data Acquisition and Advanced Computing Systems Technology and Applications Idaacs 2019, 2019
  • Using Differential Equations with Time Delay on a Hexagonal Lattice for Modeling Immunosensors
    V. Martsenyuk, A. Sverstiuk, I. S. Gvozdetska
    Cybernetics and Systems Analysis, 2019
  • RESEARCH OF GLOBAL ATTRACTABILITY OF SOLUTIONS AND STABILITY OF THE IMMUNOSENSOR MODEL USING DIFFERENCE EQUATIONS ON THE HEXAGONAL LATTICE
    Andriy Sverstiuk
    Innovative Biosystems and Bioengineering, 2019
  • An exponential evaluation for recurrent neural network with discrete delays
    V. P. Martsenyuk, A. S. Sverstiuk
    System Research and Information Technologies, 2019
  • Approach to the study of global asymptotic stability of lattice differential equations with delay for modeling of immunosensors
    Vasiliy P. Martsenyuk, Andrey S. Sverstiuk, Igor Ye. Andrushchak
    Journal of Automation and Information Sciences, 2019
  • Qualitative analysis of the hodgkin-huxley model of neuron excitability based on classification rules
    Ceur Workshop Proceedings, 2019
  • Numerical analysis of results simulation of cyber-physical biosensor systems
    Ceur Workshop Proceedings, 2019
  • Stability, bifurcation and transition to chaos in a model of immunosensor based on lattice differential equations with delay
    Vasyl Martsenyuk, Aleksandra Kłos-Witkowska, Andriy Sverstiuk
    Electronic Journal of Qualitative Theory of Differential Equations, 2018
  • On application of latticed differential equations with a delay for immunosensor modeling
    Vasiliy P. Martsenyuk, Igor Ye. Andrushchak, Petr N. Zinko, Andrey S. Sverstiuk
    Journal of Automation and Information Sciences, 2018
  • On investigation of stability and bifurcation of neural network with discrete and distributed delays
    Vasyl Martsenyuk, Igor Andrushchak, Andrii Sverstiuk, Aleksandra Klos-Witkowska
    Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics, 2018
  • On modeling predator-prey cellular automaton with help of lattice differential equations with time delay
    Vasyl Martsenyuk
    International Multidisciplinary Scientific Geoconference Surveying Geology and Mining Ecology Management Sgem, 2018

RECENT SCHOLAR PUBLICATIONS

  • Науково-аналітичне дослідження медичного застосування лазерних технологій
    ВП Марценюк, ОА Багрій-Заяць, ЗВ Махрук, АС Сверстюк, ОМ Кучвара, ...
    КОМП’ЮТЕРНО-ІНТЕГРОВАНІ ТЕХНОЛОГІЇ: ОСВІТА, НАУКА, ВИРОБНИЦТВО, 124-130 , 2026
    2026
  • Disadvantages in the professional activities of anesthesiologists and intensive care physicians: contemporary review of forensic-medical and legal practice
    VV Franchuk, PR Selskyy, AS Sverstiuk, VV Hnativ, OY Kuziv, ...
    EMERGENCY MEDICINE 22 (1), 35-43 , 2026
    2026
    Citations: 1
  • Soil quality classification from chemical composition using machine learning methods with SHAP-based explanation
    A Humeniuk, H., Tymoshchuk, D., & Sverstiuk
    Environmental Challenges 22 (1), 101404 , 2026
    2026
  • Прогнозування рівня емоційного інтелекту студентів-медиків на основі багатофакторного регресійного аналізу
    ІВ Корда, АС Сверстюк, СМ Геряк, ЛВ Багній, НІ Багній
    Україна. Здоров’я нації, 46-53 , 2025
    2025
  • ЯКІСТЬ ЖИТТЯ ДІТЕЙ З ХРОНІЧНОЮ ВТОМОЮ ТА СТРЕСОВИМИ РОЗЛАДАМИ ПІД ЧАС ВІЙНИ: СИСТЕМАТИЧНИЙ ОГЛЯД ЛІТЕРАТУРИ
    С Никитюк, С Левенець, Т Гаріян, В Синицька, А Сверстюк
    Неонатологія, хірургія та перинатальна медицина 15 (4 (58)), 204-211 , 2025
    2025
  • A Predictive Model for the Development of Long COVID in Children
    V Perestiuk, A Sverstyuk, T Kosovska, L Volianska, O Boyarchuk
    International Journal of Environmental Research and Public Health 22 (11), 1693 , 2025
    2025
    Citations: 2
  • ПІДХІД ДО ОЦІНЮВАННЯ ЕЛЕКТРОКАРДІОСИГНАЛІВ НА ОСНОВІ БАГАТОФАКТОРНОГО РЕГРЕСІЙНОГО АНАЛІЗУ ФУНКЦІЇ ЧАСОВОЇ ВАРІАБЕЛЬНОСТІ
    АС Сверстюк, ЛЄ Мосій
    Вісник Вінницького політехнічного інституту, 96-104 , 2025
    2025
    Citations: 1
  • Optimization of scientific research of theoretical and methodological foundations of the formation of a culture of personal health
    AS Sverstyuk, OA Bahrii-Zayats, SO Nykytyuk, SS Levenets, TV Hariyan, ...
    Modern Pediatrics. Ukraine, 54-62 , 2025
    2025
  • РЕЗУЛЬТАТИ ЗАСТОСУВАННЯ ІНФОРМАЦІЙНОЇ ТЕХНОЛОГІЇ ОПРАЦЮВАННЯ ТА АНАЛІЗУ ЕЛЕКТРОКАРДІОСИГНАЛІВ З ВРАХУВАННЯМ ЇХ МОРФОЛОГІЧНИХ ТА РИТМІЧНИХ ОЗНАК
    A SVERSTIUK, L MOSIY
    Computer systems and information technologies, 36-46 , 2025
    2025
    Citations: 1
  • Analysis of electricity consumption using the component method of periodically correlated random processes
    A VOLOSHCHUK, H OSUKHIVSKA, M KHVOSTIVSKYI, A SVERSTIUK
    Computer systems and information technologies, 74-82 , 2025
    2025
    Citations: 3
  • АНАЛІЗ ДОСЛІДЖЕНЬ ЖОРСТКОСТІ АРМОВАНИХ КОМПОЗИТІВ В РАДІОТЕХНІЦІ ТА МЕДИЦИНІ
    Л МОСІЙ, А СВЕРСТЮК, А РЕМЕЗ, В МАРКОВСЬКИЙ
    Herald of Khmelnytskyi National University. Technical sciences 357 (5.2), 55-71 , 2025
    2025
    Citations: 1
  • БАГАТОФАКТОРНИЙ РЕГРЕСІЙНИЙ АНАЛІЗ ДЛЯ ПРОГНОЗУВАННЯ КАРДІОЛОГІЧНОГО ДІАГНОЗУ НА ОСНОВІ ФУНКЦІЇ АМПЛІТУДНОЇ ВАРІАБЕЛЬНОСТІ
    АС Сверстюк, ЛЄ Мосій
    Вісник Вінницького політехнічного інституту, 136-145 , 2025
    2025
    Citations: 1
  • APPLICATION OF PERIODICALLY CORRELATED STOCHASTIC PROCESSES FOR FORECASTING ELECTRICITY CONSUMPTION
    А ВОЛОЩУК, Г ОСУХІВСЬКА, М ХВОСТІВСЬКИЙ, А СВЕРСТЮК
    MEASURING AND COMPUTING DEVICES IN TECHNOLOGICAL PROCESSES, 393-403 , 2025
    2025
  • МАТЕМАТИЧНА МОДЕЛЬ ВАРІАЦІЙ ЕКСТРЕМУМІВ ХАРАКТЕРИСТИЧНИХ ЗУБЦІВ ЕЛЕКТРОКАРДІОСИГНАЛІВ НА ОСНОВІ ДИСКРЕТНОЇ ФУНКЦІЇ АМПЛІТУДНОЇ ВАРІАБЕЛЬНОСТІ
    А СВЕРСТЮК, Л МОСІЙ
    Herald of Khmelnytskyi National University. Technical sciences 355 (4), 404-413 , 2025
    2025
    Citations: 1
  • ІНФОРМАЦІЙНА ТЕХНОЛОГІЯ АНАЛІЗУ ЕЛЕКТРОКАРДІОСИГНАЛІВ НА ОСНОВІ МАТЕМАТИЧНИХ МОДЕЛЕЙ ЧАСОВОЇ ТА АМПЛІТУДНОЇ ВАРІАБЕЛЬНОСТІ
    Л МОСІЙ, А СВЕРСТЮК
    Computer systems and information technologies, 36-44 , 2025
    2025
    Citations: 1
  • Vascular malformations in children: a rare case of vascular nevus and its clinical features
    MD Protsailo, YM Orel, SV Trach-Rosolovska, SO Nykytuk, AZ Mykolenko, ...
    Modern Pediatrics. Ukraine, 153-159 , 2025
    2025
  • Підхід до розроблення інформаційної технології експертного аналізу морфологічних ознак кардіосигналів на основі дискретної функції амплітудної варіабельності
    ЛЄ Мосій, АС Сверстюк
    Матеріали Міжнародної науково-технічної конференції „Фундаментальні та … , 2025
    2025
  • Antibacterial therapy for Lyme disease in children
    SO Nykytyuk, SS Levenets, TV Hariyan, IP Mironets, AS Sverstiuk
    CHILDS HEALTH 20 (3), 204-216 , 2025
    2025
  • FEATURES OF MODERN USE AND APPLICATION OF ASPECTS OF BLOCKCHAIN TECHNOLOGY
    A Sverstyuk, I Andrushchak
    Наукове видання" Експертна думка" , 2025
    2025
  • Науково-аналітичне дослідження застосування штучного інтелекту в медичній візуалізації
    САС Горкуненко А.Б.
    Комп’ютерно-інтегровані технології: освіта, наука, виробництво 58 (1), 181-187 , 2025
    2025

MOST CITED SCHOLAR PUBLICATIONS

  • Stability, bifurcation and transition to chaos in a model of immunosensor based on lattice differential equations with delay
    V Martsenyuk, A Klos-Witkowska, A Sverstiuk
    Electronic Journal of Qualitative Theory of Differential Equations 2018 (27 … , 2018
    2018
    Citations: 69
  • Study of classification of immunosensors from viewpoint of medical tasks
    VP Martseniuk, A Klos-Witkowska, AS Sverstiuk
    I. Horbachevsky Ternopil National Medical University , 2018
    2018
    Citations: 46
  • Quantitative analysis of fatty acids and monosaccharides composition in Chamerion angustifolium L. by GC/MS method
    L Slobodianiuk, L Budniak, H Feshchenko, A Sverstiuk, Y Palaniza
    2022
    Citations: 45
  • On application of latticed differential equations with a delay for immunosensor modeling
    VP Martsenyuk, IY Andrushchak, PN Zinko, AS Sverstiuk
    Journal of Automation and Information Sciences 50 (6) , 2018
    2018
    Citations: 35
  • Using differential equations with time delay on a hexagonal lattice for modeling immunosensors
    V Martsenyuk, A Sverstiuk, IS Gvozdetska
    Cybernetics and Systems Analysis 55 (4), 625-637 , 2019
    2019
    Citations: 32
  • On principles, methods and areas of medical and biological application of optical immunosensors
    VP Martsenyuk, A Klos-Witkowska, AS Sverstiuk, TV Bihunyak
    Медична інформатика та інженерія, 28-36 , 2018
    2018
    Citations: 30
  • Software for Statistical Processing and Modeling of a Set of Synchronously Registered Cardio Signals of Different Physical Nature.
    SA Lupenko, IV Lytvynenko, A Sverstiuk, B Shelestovskyi, A Horkunenko
    CMIS, 194-205 , 2021
    2021
    Citations: 29
  • Vector of diagnostic features in the form of decomposition coefficients of statistical estimates using a cyclic random process model of cardiosignal
    V Martsenyuk, A Sverstiuk, A Kłos-Witkowska, A Horkunenko, S Rajba
    2019 10th IEEE International Conference on Intelligent Data Acquisition and … , 2019
    2019
    Citations: 29
  • Approach to the study of global asymptotic stability of lattice differential equations with delay for modeling of immunosensors
    VP Martsenyuk, AS Sverstiuk, IY Andrushchak
    Journal of Automation and Information Sciences 51 (2) , 2019
    2019
    Citations: 26
  • Numerical analysis of results simulation of cyber-physical biosensor systems
    V Martsenyuk, A Klos-Witkowska, A Sverstiuk, O Bagriy-Zayats, K Nataliia, ...
    CEUR Workshop Proceedings, 149-164 , 2019
    2019
    Citations: 25
  • Stability Investigation of Biosensor Model Based on Finite Lattice Difference Equations
    V Martsenyuk, A Klos-Witkowska, A Sverstiuk
    International Conference on Difference Equations and Applications, 297-321 , 2018
    2018
    Citations: 25
  • Статистичний сумісний аналіз кардіосигналів на основі вектора циклічних ритмічно пов’язаних випадкових процесів
    СА Лупенко, ЯВ Литвиненко, АС Сверстюк
    Електроніка та системи управління 18 (4), c. 22-29 , 2008
    2008
    Citations: 25
  • Математичне та алгоритмічно-програмне забезпечення опрацювання електрокадіосигналів при фізичному навантаженні у кардiодiагностичних системах
    ВЛ Дунець, МО Хвостівський, АС Сверстюк, ЛВ Хвостівська
    ПП “Магнолія 2006” , 2022
    2022
    Citations: 24
  • Intelligent Big Data System Based on Scientific Machine Learning of Cyber-physical Systems of Medical and Biological Processes.
    VP Martsenyuk, A Klos-Witkowska, A Sverstiuk, O Bahrii-Zaiats, M Bernas, ...
    CMIS, 34-48 , 2021
    2021
    Citations: 22
  • Nonlinear analytics for electrochemical biosensor design using enzyme aggregates and delayed mass action
    V Martsenyuk, A Klos-Witkowska, S Dzyadevych, A Sverstiuk
    Sensors 22 (3), 980 , 2022
    2022
    Citations: 21
  • Сучасні тенденції, детермінанти та перспективи розвитку медичного та лікувально-оздоровчого spa-та wellness-туризму в світі
    OM Mochulska, AH Shulhai, OA Oshlianska, VI Bondarchuk, ...
    Вісник соціальної гігієни та організації охорони здоров'я України, 56-61 , 2019
    2019
    Citations: 21
  • Qualitative and Quantitative Comparative Analysis of Results of Numerical Simulation of Cyber-Physical Biosensor Systems.
    VP Martsenyuk, A Sverstiuk, O Bahrii-Zaiats, A Klos-Witkowska
    ITTAP, 134-149 , 2022
    2022
    Citations: 18
  • Integrated onto-based information analytical environment of scientific research, professional healing and e-learning of Chinese Image Medicine
    SA Lupenko, OR Orobchuk, DV Vakulenko, AS Sverstyuk, ...
    Вісник Національного університету «Львівська політехніка». Серія … , 2017
    2017
    Citations: 18
  • Neural network clustering technology for cartographic images recognition
    V Zhukovskyy, S Shatnyi, N Zhukovska, A Sverstiuk
    IEEE EUROCON 2021-19th International Conference on Smart Technologies, 125-128 , 2021
    2021
    Citations: 17
  • Operational stability study of lactate biosensors: modeling, parameter identification, and stability analysis
    V Martsenyuk, O Soldatkin, A Klos-Witkowska, A Sverstiuk, K Berketa
    Frontiers in Bioengineering and Biotechnology 12, 1385459 , 2024
    2024
    Citations: 16

GRANT DETAILS

Coordinator of the working group of the project 101233888 ERASMUS-EDU-2025-CBHE Partnerships for Transformation in Higher Education «Digi-CHange» («Digital Transformation and Curriculum Development for Healthcare Teams»)

Member of the working group of the project 101250610 ERASMUS-EDU-2025-VIRT-EXCH-NE ARIVE «Advancing Research and Innovation in Higher Education through Virtual Exchanges»

Member of the working group of the project ERASMUS-EDU-2025-VIRT-EXCH-NE No. 101253516 «Virtual Innovation and Training for Advancing Faculty Leaders, Digital Competencies, and Research Excellence (VITAL)

Member of the project of the National Foundation for Scientific Research «Development of a portable express monitoring system for the ratio of lactate and pyruvate in blood for urgent needs of clinical diagnostics» No. 2022.01/0043 (Competition «Advanced Science in Ukraine» 2023-2025").

Participant in the project of the National Research Foundation "Research on new approaches to integrating biological material with microelectronic sensors in portable systems of personalized medicine" No. 2025.07/0161 (Competition "Advanced Science in Ukraine 2026-2028").