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

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’ life, if the only way to get to work is driving. The main goal of this proposal is to investigate the role of transportation in decision making of cancer patients and their quality of life. To reach this goal, a survey and analysis utilizing the recent advances in data science. Machine learning algorithms will identify the main factors, which influence the quality of life of patients, and 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 online discussions. The website will be maintained for at least two years. By analyzing survey data, the research team will identify the areas and patients in need of free/discounted rides, particularly between their work and house.