Rok 2023

  1. Rak E., Szczur A., Bazan J. G., Bazan-Socha S., Assessment Measures of an Ensemble Classifier Based on the Distributivity Equation to Predict the Presence of Severe Coronary Artery Disease, International Journal of Applied Mathematics and Computer Science,  (2023), Vol. 33, iss. 3, p. 361-377, DOI: 10.34768/amcs-2023-0026
  2. Rak E., Sarzyński J., Evaluation Metrics for a Hybrid Classification System Based on the Distributivity Equation and the UNSW-NB15 Cyberattack Dataset, Lecture Notes in Networks and Systems (LNNS) ; Vol. 793 ; 2367-3370 ; 2367-3389 (2023)
  3. Depciuch J., Jakubczyk P., Paja W., Pancerz K., Wosiak A., Kula-Maximenko M., Yaylım İ., Gültenkin Güldal İ., Tarhan N., Hakang Mehmet Tolgahan, Sönmez D., Sarıbal D., Arıkan Soykan, Guleken Z., Correlation between human colon cancer specific antigens and Raman spectra. Attempting to use Raman spectroscopy in the determination of tumor markers for colon cancer, Nanomedicine: Nanotechnology, Biology, and Medicine, 1549-9634, Tom.3 (2023)
  4. Depciuch J., Jakubczyk P., Paja W., Pancerz K., Wosiak A., Pınar Yalçın Bahat, Ömer Faruk Toto, Huri Bulut & Zozan Guleken, Increased levels of nerve growth factor accompany oxidative load in recurrent pregnancy loss. Machine learning applied to FT-Raman spectra study, Bioprocess and Biosystems Engineering, 1615-7591, Tom 4 (2023)
  5. Kordos, D.; Krzaczkowski, P.; Rzucidło, P.; Gomółka, Z.; Zesławska, E.; Twaróg, B., Vision System Measuring the Position of an Aircraft in Relation to the Runway during Landing Approac, Sensors 2023, 23, 1560, 1424-8220, Tom 23 (2023)
  6. Depciuch J, Paja W., Pancerz K., Özgur Uzun, Huri Bulut, Nevzat Tarhan, Zozan Guleken, Analysis of follicular fluid and serum markers of oxidative stress in women with unexplained infertility by Raman and machine learning methods, Journal of Raman Spectroscopy, https://doi.org/10.1002/jrs.6510 (2023)
  7. Zozan Guleken, Jakubczyk P., Paja W., Pancerz K., Wosiak A., Nevzat Tarhan, MehmetTolgahan, Hakan Dilara, Sönmez Devrim, Sarıbal D. Soykan Arıkan, Depciuch J., An application of raman spectroscopy in combination with machine learning to determine gastric cancer spectroscopy marker, Computer Methods and Programs in Biomedicine, Volume 234, June 2023, 107523
  8. Hawro P., Kwater T., Bartman J., Kwiatkowski B., The look-up algorithm of monitoring an object described by non-linear ordinary differential equations, Bulletin of the Polish Academy of Sciences: Technical Sciences | 2023 | 71 | 2, ISSN 2300-1917
  9. Saravana Balaji B,, Paja W., Milos Antonijevic, Catalin Stoean, Nebojsa Bacanin, Miodrag Zivkovic, IoT Integrated Edge Platform for Secure Industrial Application with Deep Learning, Human-centric Computing and Information Sciences, volume 13, Article number: 19 (2023)
  10. Mokhtar K., Lopushansky A., Lopushanska H., Inverse problem for a time-fractional differential equation with a time- and space-integral conditions, Wiley, https://doi.org/10.1002/mma.9453
  11. Kozlik-Siwiec P., Buregwa-Czuma S., Zawlik I., Dziedzina S., Myszka A., Zuk-Kuwik J., Siwiec-Kozlik A. , Zarychta J., Okoń K. , Zaręba L., Soja J., Jakiela B., Kepski M., Bazan J.G.,  Bazan-Socha S., Co-Expression Analysis of Airway Epithelial Transcriptome in Asthma Patients with Eosinophilic vs. Non-Eosinophilic Airway Infiltration, International Journal of Molecular Sciences 2023, 24,3789
  12. Piechowicz B., Kwiatek A., Sadło S., Zaręba L., Koziorowska A., Kloc D., Balawejder M., Use of Gas Chromatography and SPME Extraction for the Differentiation between Healthy and Paenibacillus larvae Infected Colonies of Bee Brood—Preliminary Research, Agriculture 2023, 13, 487
  13. Przybylski A., Jagielski D., Hrymniak B., Michalak M., Wójcik T., Syska P., Fabiszak T., Rokicki J., Małecka B., Ząbek A., Kaczmarek K., Zaręba L., Sterliński M., Employment of the Evolution RL sheath as a first- hoice device shortens transvenous lead extraction time without affecting procedural safety and efficacy compared to its auxiliary use: Insights from the rospective multicenter EVO registry, Advances in Clinical and Experimental Medicine, ISSN 1899–5276, 2023
  14. Wójcik K., Bazan-Socha S., Celejewska-Wójcik N., Górka K., Lichołai K., Polok K., Stachura T., Zaręba L., Dziedzic R., Gradzikiewicz A., Sanak M. , Musiał J., Sładek T., Iwaniec T., Decreased protein C activity, lower ADAMTS13 antigen and free protein S levels accompanied by unchanged thrombin generation potential in hospitalized COVID -19 patients, Thrombosis Research, 2023
  15. Dziedzic R., Wójcik K., Olchawa M., Sarna T., Pięta J., Jakieła B., Padjas A., KoronaA., Zaręba L., Potaczek D., Kosałka-Węgiel J., Jurczyszyn A., Bazan-Socha S., Increased oxidative stress response in circulating blood of systemic sclerosis patients – relation to disease characteristics and inflammatory blood biomarkers , Seminars in Arthritis and Rheumatism, 2023
  16. Depciuch J., Czarny W., Płonka. A., Podgorski R., Bajorek W., Dziadek B., Kula-Maximenko M., Sznajderf M., Paja W., Shpotyuk Y., Cebulski J., Krol P., Investigation of novel methods for stress level measurements in athletes employing FTIR and Raman spectroscopy techniques, Measurement, 2023
  17. Zozan Guleken, Gizem Suna, S¸ ahika Burcu Karaca, Huri Bulut, Ceylan Ayada, Pancerz K., Paja W., Jakubczyk P., Wrobel T., Cebulski J., Depciuch J., FTIR, RAMAN and biochemical tools to detect reveal of oxidative Stress-Related lipid and protein changes in fibromyalgia, Infrared Physics and Technology 2023
  18. Paja W., Application of the Fuzzy Approach for Evaluating and Selecting Relevant Objects, Features, and Their Ranges, Entropy 2023
  19. Paja W., Szkoła J., Pancerz K., Sarzyński J., Żychowska M, Identification of Melanocytic Skin Lesions Using Deep Learning Methods, Seria: Monografie Politechniki Łódzkiej Nr. 2437, Wydawnictwo Politechniki Łódzkiej, Łódź 2023
  20. Krzysztof P., Andrzej B., Grochowalski P., Paja W., Ontologiczny generator testów wiedzy z tekstów na przykładzie wiedzy o geografii Polski, Barometr Regionalny. Analizy I Prognozy, 19(1), 41–49, 2023
  21. Paja W., Application of the Fuzzy Approach for Evaluating and Selecting Relevant Objects, Features, and Their Ranges, Entropy 2023   
  22. Paja W., Szkoła J., Pancerz K., Sarzyński J., Żychowska M., Identification of Melanocytic Skin Lesions Using Deep Learning Methods, Seria: Monografie Politechniki Łódzkiej Nr. 2437, Wydawnictwo Politechniki Łódzkiej, Łódź 2023
  23. Kluz‑Barłowska M., Kluz T., Paja W., Sarzyński J., Łączyńska‑Madera M., Odrzywolski A., Król P., Cebulski J., Depciuch J., FT‑Raman data analyzed by multivariate and machine learning as a new methods for detection spectroscopy marker of platinum‑resistant women sufering from ovarian cancer Nature.com/Scientific Reports, 2023
  24. PrzybylskiA., Jagielski D., Hrymniak B., Michalak M., Wójcik T., Syska P., Fabiszak T., Rokicki J., Małecka B., Ząbek A., Kaczmarek K., Zaręba L., Sterliński M., Employment of the Evolution RL sheath as a first- hoice device shortens transvenous lead extraction time without affecting procedural safety and efficacy compared to its auxiliary use: Insights from the  rospective multicenter EVO registry, Advances in Clinical and Experimental Medicine, ISSN 1899–5276, 2023
  25. Mizera D., Dziedzic R., Drynda A., Gradzikiewicz A., Jakieła B., Celińska-Löwenhoff M., Padjas A., Matyja-Bednarczyk A., Zaręba L., Bazan-Socha S., Cellular immune response to SARS-CoV-2 in patients with primary antibody deficiencies Frontiers in immunology, 2023
  26. Dziedzic R., Zaręba L., Iwaniec T., Kubicka-Trząska A., Romanowska-Dixon B., Bazan-Socha S., Dropiński J., High prevalence of thrombophilic risk factors in patients with central retinal artery occlusion, Thrombosis Journal 21, Article number: 81 (2023)
  27. Drygaś P. Uninorms and their applications, Wydawnictwo Uniwersytetu Rzeszowskiego, Rzeszów 2023, ISBN 978–83–8277–117–6
  28. Paja W., Szkoła J., Pancerz K., Sarzyński J., Żychowska M., A Preliminary Research on Automatic Identification of Melanocytic Skin Lesions from Digital Images, Procedia Computer Science 225 (2023) 4706–4712
  29. Paja W., Pancerz K., Jakubczyk P., Determining Reference Spectra for Medical Diagnosis Using Clustering Methods, Procedia Computer Science 225 (2023) 4700–4705
  30. Bazan, J.G., Milan, P., Bazan-Socha, S., Wójcik, K.: Application of Federated Learning to Prediction of Patient Mortality in Vasculitis Disease. In: Campagner, A., Urs Lenz, O., Xia, S., Ślęzak, D., Wąs, J., Yao, J. (eds) Rough Sets. IJCRS 2023. Lecture Notes in Computer Science, vol 14481, pp. 526–536. Springer (2023)
  31. Bazan, J., G., Bazan-Socha, S., Bentkowska, U., Gałka, W., Mrukowicz, M., Zarȩba, L.: Aggregation Functions in Researching Connections Between Bio-Markers and DNA Micro-arrays. In: Atanassov, K.T., et al. Uncertainty and Imprecision in Decision Making and Decision Support - New Advances, Challenges, and Perspectives. IWIFSGN BOS/SOR 2022 2022. Lecture Notes in Networks and Systems, vol 793, pp 106–115. Springer (2023)
  32. Bentkowska, U., Mrukowicz, M. (2023). Parameterized Interval-Valued Aggregation Functions in Classification of Data with Large Number of Missing Values. In: Atanassov, K.T., et al. Uncertainty and Imprecision in Decision Making and Decision Support - New Advances, Challenges, and Perspectives. IWIFSGN BOS/SOR 2022 2022. Lecture Notes in Networks and Systems, pp. 85-94, vol 793. Springer, Cham
  33. International Symposium on Fuzzy Sets – Uncertainty Modelling. Abstratcs, U. Bentkowska, P. Drygaś, A. Król, B. Pękala, E. Rak (Eds.), University of Rzeszów, Rzeszów, Poland,  All papers have been reviewed, pages 1-75, May 19-21, 2023, Wydawnictwo Uniwersytetu Rzeszowskiego, Rzeszów, ISBN 978-83-8277-077-3
  34. Zeslawska, E., Gomolka, Z., Dydek-Dyduch, E. (2024). Application of ALMM Technology to Intelligent Control System for a Fleet of Unmanned Aerial Vehicles. In: Luo, B., Cheng, L., Wu, ZG., Li, H., Li, C. (eds) Neural Information Processing. ICONIP 2023. Communications in Computer and Information Science, vol 1963. Springer, Singapore