Modeling the Dynamics of Cancerous Tumors in Vivo
Durrett, Richard T
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A key area of interest in cancer research is understanding tumor dynamics, so that tumor growth can be predicted more easily and treated more reliably. We explored in vivo tumor dynamics starting from simple exponential and logistic growth and progressing to more general models. We then applied these models to analyze the growth of breast cancer, liver cancer, and two types of neurological cancer using five data sets. We found that exponential growth gave the best fit to breast and liver cancers, while surface growth (a 2/3's power law) gave the best fit to neurological cancers.
CitationTalkington, Anne (2015). Modeling the Dynamics of Cancerous Tumors in Vivo. Honors thesis, Duke University. Retrieved from http://hdl.handle.net/10161/10786.
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This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 3.0 United States License.
Rights for Collection: Undergraduate Honors Theses and Student papers