Exploring the Role of Transportation on Cancer Patient Decision-making through Machine Learning Techniques

Project ID: CTEDD 019-15

Author(s): Roya Etminani, University of Texas at Arlington

Co-Author(s): Leili Shahriyari, University of Texas at Arlington

CTEDD Funding Year: 2019 General RFP

Project Status: Complete

UTC Funding: $240,870

End Date: May 31, 2020

One of the main challenges of cancer patients is making decisions simultaneously about their cancer treatments and careers because of many factors, including side-effects and the cost of treatments. For example, the most common side-effect of cancer treatments is dizziness, which reduces the ability of patients in driving. This minor side effect might completely change cancer patients’ lives if their only mode of transportation is driving.

The main goal of this project is to investigate the role of transportation in the decision-making of cancer patients and their quality of life. To reach this goal, a we propose to undertake a survey and analysis utilizing the most recent advances in data science. Machine learning algorithms will identify the main factors that influence the quality of life of patients, as well as the relationship of these factors with each other.

Furthermore, advances in information and communication technology (ICT) will be used to create a website to collect the data, provide reports, and foster online discussions. The website will be maintained for at least two years. By analyzing the survey data, we will identify the specific areas and patient profiles in need of free/discounted rides, particularly for work-related as well as health-related trips.