Document Type
Honors Thesis
Abstract
We formulated a new and efficient method to propose a personalized treatment platform for colorectal cancer. A mathematical model of colon cancer was used and is comprised of a system of differential equations, which model various cell dynamics. The dynamics are dependent on patient-specific parameters that are unknown which we estimate given patient data in form of cell measurements. We approached this estimation as an inverse problem based on an optimization framework and developed computational optimization techniques created on non-linear conjugate gradient methods to solve for the optimal set of parameters for a specific patient. These optimal parameters are then ranked by conducting a sensitivity analysis using the Latin Hypercube Sampling-Partial Rank Correlation Coefficient method, to determine the most sensitive parameters with respect to the tumor cell count. Using this information, we can deduce the types of feasible treatment strategies which can be utilized for curing the patient.
Publication Date
12-1-2021
Language
English
License
This work is licensed under a Creative Commons Attribution-NonCommercial-Share Alike 4.0 International License.
Recommended Citation
Manoj, Achyuth, "PARAMETER ESTIMATION AND SENSITIVITY ANALYSIS THROUGH MATHEMATICAL MODELING OF COLON CANCER" (2021). 2021 Fall Honors Capstone Projects. 24.
https://mavmatrix.uta.edu/honors_fall2021/24