2023
DOI: 10.1016/j.compbiomed.2022.106481
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Cellular-automaton model for tumor growth dynamics: Virtualization of different scenarios

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Cited by 14 publications
(3 citation statements)
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“…CA has applications in diverse fields, including physics, biology, and computer science. The main applications of CA include modeling physical phenomena, such as fluid flow and heat diffusion [ 27 ], simulating biological systems, such as cellular growth and population dynamics [ 28 ], and exploring emergent behaviors in complex systems, such as traffic flow or urban development [ 29 ]. CA's ability of CA to capture complex patterns and behaviors emerging from simple local interactions makes it a valuable tool for modeling, simulating, and analyzing dynamic systems in various scientific and computational domains.…”
Section: Introductionmentioning
confidence: 99%
“…CA has applications in diverse fields, including physics, biology, and computer science. The main applications of CA include modeling physical phenomena, such as fluid flow and heat diffusion [ 27 ], simulating biological systems, such as cellular growth and population dynamics [ 28 ], and exploring emergent behaviors in complex systems, such as traffic flow or urban development [ 29 ]. CA's ability of CA to capture complex patterns and behaviors emerging from simple local interactions makes it a valuable tool for modeling, simulating, and analyzing dynamic systems in various scientific and computational domains.…”
Section: Introductionmentioning
confidence: 99%
“…To couple the microscopic scale of cancer invasion, discrete models were developed. Following the discrete approach, it becomes straightforward to achieve quantification and visualization of cell growth, deformation, movement, and interactions during cancer invasion (Chen et al 2020;Smeets et al 2016;Valentim et al 2023). Nevertheless, solving the discrete model, particularly with largescale populations, demands substantial computing resources and time.…”
Section: Introductionmentioning
confidence: 99%
“…The fractional order differential equations have been used in various applications including biomedical engineering, economics, and control theory [15][16][17]. Both continuous and discrete fractional-order models have been employed in the study of cancer [18][19][20][21], but discrete fractional models are arguably superior in capturing the tumor growth dynamics [22][23][24]. Discrete models can better account for the natural time delays and discrete nature of cell proliferation and death, and they are better suited for simulating the discrete nature of data collection [25][26][27].…”
Section: Introductionmentioning
confidence: 99%