Analytics and Decision-Making in Healthcare
The need for healthcare analytics and its connection with optimal decision-making is growing very rapidly. The goal of this course is to walk the student through the journey form data analytics (using Machine Learning (ML)/Artificial Intelligence (AI) techniques) to decision analytics (using optimization techniques). In doing so, it teaches the students how to use healthcare data and analytical modeling to understand healthcare systems, predict healthcare outcomes, and make informed, optimal decisions to transform healthcare delivery for individuals and populations. Therefore, it explores the role of ML/AI in supporting data-driven decision-making in healthcare systems. To this end, the course equips the students with analytical thinking and problem-solving mindset for a wide range of purposes/applications, including descriptive, predictive, and prescriptive analytics. Using numerous applications in healthcare, various techniques for healthcare data analytics and decision analysis are taught. This course covers topics such as descriptive analytics using data visualization, predictive analytics using regression and classification, and prescriptive analytics using decision trees, simulation, and basic linear programming.
- Prerequisite: C650