چکیده مقاله
Mathematical modeling has matured into an essential pillar of oncology, offering powerful in silico laboratories to dissect the complexities of carcinogenesis and, crucially, to design and test intervention strategies This paper provides a comprehensive exploration of the mathematical formalisms used in cancer dynamics, with a particular focus on literature published since 2022 We systematically review a wide spectrum of models, including deterministic and stochastic ordinary differential equations ODES , continuum models based on partial differential equations PDEs , discrete approaches such as cellular automata and network models, and sophisticated individual based systems like agent based models ABMs We analyze how each paradigm can be applied to simulate critical strategies in cancer dynamics, from optimizing chemopreventive drug regimens to modeling the impact of dietary interventions on cellular signaling networks The challenges of model parameterization, validation, and the increasing synergy with artificial intelligence are discussed in detail We posit that the future of effective, personalized cancer modeling lies not in a single 'best' model, but in the strategic development and integration of validated, AI driven hybrid models that can create high fidelity 'digital twins' to forecast individual cancer risk and response to intervention
کلیدواژهها
نویسندگان
Elahe Ghiyabi
Department of Biomedical Engineering, Faculty of Electrical and Computer Engineering, University of Tabriz, Tabriz, Iran
Sajjad Mortazavi
Department of Biomedical Engineering, Faculty of Electrical and Computer Engineering, University of Tabriz, Tabriz, Iran
Kosar Tanhaei
Department of Electrical Engineering, Faculty of Electrical and Computer Engineering, University of Shahed, Tehran, Iran
شیوه ارجاع
Ghiyabi, Elahe and Mortazavi, Sajjad and Tanhaei, Kosar,1404,Bridging Dimensions: From Mechanistic ODES to Agent-Based Systems in Modeling Cancer Dynamics,The Second International Congress of Cancer,Zanjan
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