Description: Understand the role of AI and machine learning in healthcare and policy, focusing on opportunities, limitations, and real-world applications. Through case studies,
discussions, projects, and speaker sessions, students will gain a nuanced understanding of AI’s role in healthcare
transformation, complemented by exposure to relevant programming tools.
Learning Objectives: Get a basic understanding of application of Machine Learning techniques: Identify key machine learning methods,
understand their application in healthcare delivery, clinical decision-making, and risk prediction, and apply these
techniques to health data
- Critically Evaluate AI/ML in Healthcare: Analyze and critique the use of AI/ML in various domains of healthcare and
health policy, understanding both its potential benefits and limitations.
- Address Ethical and Social Implications: Evaluate the fairness, bias, and privacy concerns in AI applications, and
understand the ethical and policy considerations relevant to healthcare
- Gain introductory exposure to data analysis tools: Develop basic proficiency in using features of programming
tools such as R to apply to relevant health data problems
- Engage in Professional Development through Invited Guests and Project Work: Collaborate on a group project that
explores a pressing AI/health policy topic, incorporating a data analysis component, and presenting findings
through both written and oral presentations
- Communicate Effectively in AI and Health Policy Contexts: Communicate complex AI/ML concepts clearly to both
technical and non-technical audiences, and participate effectively in discussions around AI’s impact on healthcare.
