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Please use this identifier to cite or link to this item: http://arks.princeton.edu/ark:/88435/dsp01tb09j809t
Title: An Analysis of Thyroid Cancer Incidence and Treatment Classification
Authors: Barcicki Kaskiewicz, Natalie
Advisors: Massey, William
Department: Operations Research and Financial Engineering
Class Year: 2016
Abstract: Although surgery is the primary treatment for patients diagnosed with thyroid cancer, the extent of the required surgery remains controversial. This thesis presents a statistical analysis of thyroid cancer incidence and management costs in order to identify commonly-associated risk factors with the development of the disease, and to motivate the necessity for improvements in treatment recommendations. In an at- tempt to determine the optimal treatment given the features of a diagnosed patient, it employs statistical and machine learning techniques, including principal compo- nent analysis, logistic regression, least absolute shrinkage and selection operator, and support vector machines, to create different models that predict treatment recom- mendations from a computational perspective. The models developed are restricted to binary classification of either a total thyroidectomy recommendation or not. The results do not resolve the debate with regards to thyroid cancer treatment, but pro- vide a strong foundation for moving forward in applying computational techniques to the problem.
Extent: 54 pages
URI: http://arks.princeton.edu/ark:/88435/dsp01tb09j809t
Type of Material: Princeton University Senior Theses
Language: en_US
Appears in Collections:Operations Research and Financial Engineering, 2000-2016

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