Applications of Stochastic Processes to Cancer Research

dc.contributor.advisor	Pravica, David W.	en_US
dc.contributor.author	Steely, Kristin Michelle	en_US
dc.contributor.department	Mathematics	en_US
dc.date.accessioned	2013-06-06T12:18:54Z
dc.date.available	2013-06-06T12:18:54Z
dc.date.issued	2013	en_US
dc.description.abstract	The purpose of this thesis is to implement stochastic models that are currently used to analyze the impact of different drug treatments on cancer and to model drug resistance by cancer cells. Mathematical models are used to compare single-cancer treatment results with those that involve multiple drugs at the same time. Using various parameters for the model, the probability of treatment success was calculated. A comparison was made with a probability theory approach and good agreement was obtained.	en_US
dc.description.degree	M.A.	en_US
dc.format.extent	51 p.	en_US
dc.format.medium	dissertations, academic	en_US
dc.identifier.uri	http://hdl.handle.net/10342/1764
dc.language.iso		en_US
dc.publisher	East Carolina University	en_US
dc.subject	Mathematics	en_US
dc.subject	Applied mathematics	en_US
dc.subject	Medicine	en_US
dc.subject	Kolmogorov forward equation	en_US
dc.subject	Markov processes	en_US
dc.subject	Ordinary differential equations	en_US
dc.subject	Partial differential equations	en_US
dc.subject	Probability generating function	en_US
dc.subject	Stochastic processes	en_US
dc.subject.lcsh	Stochastic analysis
dc.subject.lcsh	Drug resistance in cancer cells
dc.title	Applications of Stochastic Processes to Cancer Research	en_US
dc.type	Master's Thesis	en_US

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