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Computational algorithms for the analysis of cancer virotherapy model

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dc.contributor.author Raza, Ali
dc.contributor.author Baleanu, Dumitru
dc.contributor.author Rafiq, Muhammad
dc.contributor.author Abbas, Syed Zaheer
dc.contributor.author Siddique, Abubakar
dc.contributor.author Javed, Umer
dc.contributor.author Naz, Mehvish
dc.contributor.author Fatima, Arooj
dc.contributor.author Munawar, Tayyba
dc.contributor.author Batool, Hira
dc.contributor.author Nazir, Zaighum
dc.date.accessioned 2024-02-29T12:04:41Z
dc.date.available 2024-02-29T12:04:41Z
dc.date.issued 2022
dc.identifier.citation Raza, Ali;...et.al. (2022). "Computational algorithms for the analysis of cancer virotherapy model", Computers, Materials and Continua, Vol.71, No.2, pp.3621-3634. tr_TR
dc.identifier.issn 15462218
dc.identifier.uri http://hdl.handle.net/20.500.12416/7396
dc.description.abstract Cancer is a common term for many diseases that can affect any part of the body. In 2020, ten million people will die due to cancer. A worldwide leading cause of death is cancer by theWorld Health Organization (WHO) report. Interaction of cancer cells, viral therapy, and immune response are identified in this model. Mathematical and computational modeling is an effective tool to predict the dynamics of cancer virotherapy. The cell population is categorized into three parts like uninfected cells (x), infected cells (y), virus-free cells (v), and immune cells (z). The modeling of cancerlike diseases is based on the law of mass action (the rate of change of reacting substances is directly proportional to the product of interacting substances). Positivity, boundedness, equilibria, threshold analysis, are part of deterministic modeling. Later on, a numerical analysis is designed by using the standard and non-standard finite difference methods. The non-standard finite difference method is developed to study the long-term behavior of the cancer model. For its efficiency, a comparison of the methods is investigated. tr_TR
dc.language.iso eng tr_TR
dc.relation.isversionof 10.32604/cmc.2022.023286 tr_TR
dc.rights info:eu-repo/semantics/openAccess tr_TR
dc.subject Algorithms tr_TR
dc.subject Cancer Disease tr_TR
dc.subject Epidemic Model tr_TR
dc.subject Stability Analysis tr_TR
dc.title Computational algorithms for the analysis of cancer virotherapy model tr_TR
dc.type article tr_TR
dc.relation.journal Computers, Materials and Continua tr_TR
dc.contributor.authorID 56389 tr_TR
dc.identifier.volume 71 tr_TR
dc.identifier.issue 2 tr_TR
dc.identifier.startpage 3621 tr_TR
dc.identifier.endpage 3634 tr_TR
dc.contributor.department Çankaya Üniversitesi, Fen Edebiyat Fakültesi, Matematik Bölümü tr_TR


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