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Special Topics: Designing Smart and Healthy Systems

90-835

Units: 3

Description

Classes held in person from 9 AM- 4:30 PM on Saturdays of March 30 and April 20, 2024, room TBD, and in one on-line session on Saturday, April 6. 

This course will give students with no previous experience in artificial intelligence a chance to learn about applications of AI to health care. Drawing on consulting experience for healthcare clients, this course will survey several real-life healthcare applications of AI capabilities, including predictive modeling, intelligent computer interaction, social network analysis, computer vision, and large language models. Along the way, we will also discuss concepts from behavioral economics, causal inference, gamification and more. Beyond introducing students to the field, the course aims to build critical thinking skills, so for their final project, teams of students will describe an AI healthcare application and a critical evaluation of claims made by researchers or vendors for that application

Learning Outcomes

The main learning objectives of the course are to:

  1. Describe a range of real-world applications of AI to healthcare including both achievements and challenges faced.
  2. Understand why large language models have generated such excitement for health care, along with limitations and risks of the technology.
  3. Apply a range of techniques for evaluating AI healthcare applications and results, including experimental design, and causal inference.

Prerequisites Description

None, but a basic knowledge of statistics (such as statistical significance) will be helpful for the material on evaluating applications.

Syllabus