Naïve Bayes Classification for Analyzing Prostate Cancer Treatment Outcomes
Description
Prostate cancer is the second most common kind of cancer in men. Fortunately, it has a 99% survival rate. To achieve such a survival rate, a variety of aggressive therapies are used to treat prostate cancers that are caught early. Androgen deprivation therapy (ADT) is a therapy that is given in cycles to patients. This study attempted to analyze what factors in a group of 79 patients caused them to stick with or discontinue the treatment. This was done using naïve Bayes classification, a machine-learning algorithm. The usage of this algorithm identified high testosterone as an indicator of a patient persevering with the treatment, but failed to produce statistically significant high rates of prediction.
Date Created
The date the item was original created (prior to any relationship with the ASU Digital Repositories.)
2016-12
Agent
- Author (aut): Millea, Timothy Michael
- Thesis director: Kostelich, Eric
- Committee member: Kuang, Yang
- Contributor (ctb): Computer Science and Engineering Program
- Contributor (ctb): Barrett, The Honors College