Advisor | Pravica, David W. | en_US |
Author | Steely, Kristin Michelle | en_US |
Date Accessioned | 2013-06-06T12:18:54Z | |
Date Available | 2013-06-06T12:18:54Z | |
Date of Issue | 2013 | en_US |
Identifier (URI) | http://hdl.handle.net/10342/1764 | |
Description | 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 |
Extent | 51 p. | en_US |
Format Medium | dissertations, academic | en_US |
Language | | en_US |
Publisher | East Carolina University | en_US |
Subject | Mathematics | en_US |
Subject | Applied mathematics | en_US |
Subject | Medicine | en_US |
Subject | Kolmogorov forward equation | en_US |
Subject | Markov processes | en_US |
Subject | Ordinary differential equations | en_US |
Subject | Partial differential equations | en_US |
Subject | Probability generating function | en_US |
Subject | Stochastic processes | en_US |
Library of Congress Subject Headings | Stochastic analysis | |
Library of Congress Subject Headings | Drug resistance in cancer cells | |
Title | Applications of Stochastic Processes to Cancer Research | en_US |
Type | Master's Thesis | en_US |
Department | Mathematics | en_US |
Degree | M.A. | en_US |