References
- Kuzomin O, Abu-Jassar AT, Lyashenko V. Forecasting and decision making in the context of COVID. Int J Acad Inf Syst Res. 2023;7(6):89-94.
- Abu-Jassar AT, Sotnik S, Sinelnikova T, Lyashenko V. Binarization methods in multimedia systems when recognizing license plates of cars. Int J Acad Eng Res. 2023;7(2):1-9.
- Markushevska АV, Savchenko МО. Mathematical simulation of blood movement in vessels. Bull Stud Sci Soc. 2021;2(13):316-319.
- Morozova ОМ, Batyuk LV, Muraveinik ОА. Mathematical modeling of red blood cell shape change in early neuroprotection with moderate therapeutic effect of hypothermia. Probl Cryobiol Cryomed. 2020;30(3):290. https://doi.org/10.15407/cryo30.03.290
- Batyuk LV, Kizilova NМ. Modeling of blood cell surface oscillations as fluid-filled multilayer viscoelastic shells. Bull Taras Shevchenko Natl Univ Kyiv Ser: Phys Math. 2022;1:40-43. https://doi.org/10.17721/1812-5409.2022/1.4
- Novytskyy VV, Novytskyy Jr VV. Mathematical model of erythrocyte in the capillary motion. Bull Taras Shevchenko Natl Univ Kyiv Ser Phys Math. 2021;4:56-61. https://doi.org/10.17721/1812-5409.2021/4.8
- Batyuk LV, Kizilova NМ. Modeling of laminar flows of erythrocyte suspensions as Binhgam microfluids. Bull Taras Shevchenko Natl Univ Kyiv Ser: Phys Math. 2017;4:23-28.
- Pertsov ОV, Berest VP. Analysis of kinetics of light scattering by cell suspection during aggregation: Mathematical modeling of platelet disaggregation. Visnyk of VN Karazin Kharkiv Natl Univ, Ser “Radio Phys Electron.”. 2021;34:70-77. https://doi.org/10.26565/2311-0872-2021-34-08
- Cao B, Zhang H, Wang N, Gao X, Shen D. Auto-GAN: Self-supervised collaborative learning for medical image synthesis. Proceed of the AAAI Conf AI. 2020;34(7):10486-10493. https://doi.org/10.1609/aaai.v34i07.6619
- Ko BC, Gim JW, Nam JY. Automatic white blood cell segmentation using stepwise merging rules and gradient vector flow snake. Micron. 2011;42(7):695-705. https://doi.org/10.1016/j.micron.2011.03.009
- Shah A, Naqvi S, Naveed K, Salem N, Khan M, Alimgir K. Automated Diagnosis of Leukemia: A Comprehensive Review. IEEE Access. 2021;9:132097-132124. https://doi.org/10.1109/ACCESS.2021.3114059
- Navya KT, Prasad K, Singh BMK. Analysis of red blood cells from peripheral blood smear images for anemia detection: A methodological review. Med Biol Eng Comput. 2022;60(9):2445-2462. https://doi.org/10.1007/s11517-022-02614-z
- Basu A, Senapati P, Deb M, Rai R, Dhal KG. A survey on recent trends in deep learning for nucleus segmentation from histopathology images. Evolving Systems. 2024;15:203-248. https://doi.org/10.1007/s12530-023-09491-3
- World Medical Association. 2022. WMA Declaration Helsinki – Ethical Princ. Med. Research Involv. Human Subj. https://www.wma.net/policies-post/wma-declaration-of-helsinki-ethical-principles-for-medical-research-involving-human-subjects/
- Mohapatra S, Patra D. Automated leukemia detection using hausdorff dimension in blood microscopic images. In: Proceed Int Conf IEEE Robotics and Commun Technol (INTERACT-2010). 2010:64-68. https://doi.org/10.1109/INTERACT.2010.5706196
- Li Y, Zhu R, Mi L, Cao Y, Yao D. Segmentation of white blood cell from acute lymphoblastic leukemia images using dual-threshold method. Comput. Math. Methods Med. 2016;9514707. https://doi.org/10.1155/2016/9514707
- Wang Y, Cao Y. Quick leukocyte nucleus segmentation in leukocyte counting. Comput Math Methods Med. 2019;3072498. https://doi.org/10.1155/2019/3072498
- Yang Y, Cao Y, Shi W. A method of leukocyte segmentation based on S component and B component images. J Innovative Opt Health Sci. 2014;7(1):1450007. https://doi.org/10.1142/S1793545814500072
- Rabotiahov A, Kobylin O, Dudar Z, Lyashenko V. Bionic image segmentation of cytology samples method. In: 2018 14th Int Conf Adv Trends Radioelecrtron, Telecommun Comp Eng (TCSET). 2018;665-670. https://doi.org/10.1109/TCSET.2018.8336289
- Lyashenko V, Rabotiahov A, Kobylin О, Kolesnykov D. Analysis of human speech as a protection tool in infocommunication systems. In: 2018 Int Sci-Pract Conf “Probl Infocommun Sci Tech”. 2018;79-83. https://doi.org/10.1109/INFOCOMMST.2018.8632156
- Wang H, Ma H, Fang P, et al. Dynamic confocal Raman spectroscopy of flowing blood in bionic blood vessel. Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy. 2021;259:119890. https://doi.org./10.1016/j.saa.2021.119890
- Li J, Ye W, Fan Z, Cao L. A Novel Stereocomplex Poly(lactic acid) with Shish-Kebab Crystals and Bionic Surface Structures as Bioimplant Materials for Tissue Engineering Applications. ACS Appl Mater Interfaces. 2021;13(4):5469-5477. https://doi.org/10.1021/acsami.0c17465
- Li Z, Wu T, Chen Y, Gao X, Ye J, Jin Y, Chen B. Oriented homo-epitaxial crystallization of polylactic acid displaying a biomimetic structure and improved blood compatibility. J Biomed Mater Res: Part A. 2022;110(3):684-695. https://doi.org/10.1002/jbm.a.37322
- Chen Y, Yang W, Hu Z, et al. Preparation and properties of oriented microcellular Poly(l-lactic acid) foaming material. International Journal of Biological Macromolecules. 2022;211:460-469. https://doi.org/10.1016/j.ijbiomac.2022.05.075
- Zhao X, Li J, Liu J, Zhou W, Peng S. Recent progress of preparation of branched poly(lactic acid) and its application in the modification of polylactic acid materials. Int J Biol Macromol. 2021;193(Part A):874-892. https://doi.org/10.1016/j.ijbiomac.2021.10.154
- Li Z, Ye L, Zhao X, Coates P, Caton-Rose F, Martyn M. High orientation of long chain branched poly (lactic acid) with enhanced blood compatibility and bionic structure. J Biomed Mater Res: Part A. 2016;104(5):1082-1089. https://doi.org/10.1002/jbm.a.35640
- Li J, Chen Q, Zhang Q, Fan T, Gong L, Ye W, Fan Z, Cao L. Improving mechanical properties and biocompatibilities by highly oriented long chain branching poly(lactic acid) with bionic surface structures. ACS Appl Materials & Interfaces. 2020;12(12):14365-14375. https://doi.org/10.1021/acsami.9b20264
- Huang L, Tan J, Li W, Zhou L, Liu Z, Luo B, Lu L, Zhou, C. Functional polyhedral oligomeric silsesquioxane reinforced poly(lactic acid) nanocomposites for biomedical applications. J Mech Behav Biomed Mater. 2019;90:604-614. https://doi.org/10.1016/j.jmbbm.2018.11.002
- Li J, Zhao X, Ye L, Coates P, Caton-Rose F. Multiple shape memory behavior of highly oriented long-chain-branched poly(lactic acid) and its recovery mechanism. J Biomed Mater Res: Part A. 2019;107(4):872-883. https://onlinelibrary.wiley.com/doi/10.1002/jbm.a.36604
- Wang K, Lu J, Tusiime R, Yang Y, Fan F, Zhang H, Ma B. Properties of poly (L-lactic acid) reinforced by L-lactic acid grafted nanocellulose crystal. Int J Biol Macromol. 2020;156:314-320. https://doi.org/10.1016/j.ijbiomac.2020.04.025
- Zheng BD, Xiao MT. Red blood cell membrane nanoparticles for tumor phototherapy. Colloids Surfaces B: Biointerfaces. 2022;220:112895. https://doi.org/10.1016/j.colsurfb.2022.112895
- Zhu Z, Zhai Y, Hao Y, Wang Q, Han F, Zheng W, Hong J, Cui L, Jin W, Ma S, Yang L, Cheng G. Specific anti-glioma targeted-delivery strategy of engineered small extracellular vesicles dual-functionalised by Angiopep-2 and TAT peptides. J Extracell Vesicles. 2022;11(8):e12255. https://doi.org/10.1002/jev2.12255
- Miao Y, Yang Y, Guo L, Chen M, Zhou X, Zhao Y, Nie D, Gan Y, Zhang X. Cell membrane-camouflaged nanocarriers with biomimetic deformability of erythrocytes for ultralong circulation and enhanced cancer therapy. ACS Nano. 2022;16(4):6527-6540. https://doi.org/10.1021/acsnano.2c00893
- Meng Q, Pu L, Lu Q, Wang B, Li S, Liu B, Li F. Morin hydrate inhibits atherosclerosis and LPS-induced endothelial cells inflammatory responses by modulating the NFκB signaling-mediated autophagy. Int Immunopharmacol. 2022;100:108096. https://doi.org/10.1016/j.intimp.2021.108096
- Huang Y, Wu H, Xie N, Zhang X, Zou Z, Deng M, Cheng W, Guo X, Ding S, Guo B. Conductive antifouling sensing coating: A bionic design inspired by natural cell membrane. Adv Healthcare Mater. 2023;12(13):2202790. https://doi.org/10.1002/adhm.202202790
- Zhao Z, Pan M, Qiao C, Xiang L, Liu X, Yang W, Chen XZ, Zeng H. Bionic engineered protein coating boosting anti-biofouling in complex biological fluids. Adv Mater. 2023;35(6):2208824. https://doi.org/10.1002/adma.202208824
- Liu B, Tao C, Wu Z, Yao H, Wang DA. Engineering strategies to achieve efficient in vitro expansion of haematopoietic stem cells: Development and improvement. J Mater Chem B. 2022;10(11):1734-1753. https://doi.org/10.1039/D1TB02706A
- Chatterjee C, Schertl P, Frommer M, et al. Rebuilding the hematopoietic stem cell niche: Recent developments and future prospects. Acta Biomaterialia. 2021;132:129-148. https://doi.org/10.1016/j.actbio.2021.03.061
- Bello AB, Park H, Lee SH. Current approaches in biomaterial-based hematopoietic stem cell niches. Acta Biomaterialia. 2018;72:1-15. https://doi.org/10.1016/j.actbio.2018.03.028
- Gilchrist AE, Harley BAC. Connecting secretome to hematopoietic stem cell phenotype shifts in an engineered bone marrow niche. Integr Biol. 2020;12(7):175-187. https://doi.org/10.1093/intbio/zyaa013
- Zhang X, Cao D, Xu L, et al. Harnessing matrix stiffness to engineer a bone marrow niche for hematopoietic stem cell rejuvenation. Cell Stem Cell. 2023;30(4):378-395. https://doi.org/10.1016/j.stem.2023.03.005
- Mousavi SMH, Lyashenko VV, Ilanloo A, Mirinezhad SY. Fatty liver level recognition using Particle Swarm optimization (PSO) image segmentation and analysis. In: 2022 12th Int Conf Comput Knowl Eng (ICCKE). 2022;237-245. https://doi.org/10.1109/ICCKE57176.2022.9960108
- Matern F, Riess C, Stamminger, M. Gradient-based illumination description for image forgery detection. IEEE Transactions Inf Forensics Security. 2019;15:1303-1317. https://doi.org/10.1109/TIFS.2019.2935913
- Liao M, Wan Z, Yao C, Chen K, Bai X. Real-time scene text detection with differentiable binarization. Proceed AAAI Conf AI. 2020;34(7):11474-11481. https://doi.org/10.1609/aaai.v34i07.6812
- Su Y, Zang Y, Su Q, Peng L. A method for expanding the training set of white blood cell images. J Healthcare Eng. 2022;1267080. https://doi.org/10.1155/2022/1267080
- Patil AM, Patil MD, Birajdar GK. White blood cells image classification using deep learning with canonical correlation analysis. IRBM. 2021;42(5):378-389. https://doi.org/10.1016/j.irbm.2020.08.005