Weiguang Wang, Ph.D. , Computers and Information Systems group at the Simon Business School, University of Rochester.

Healthcare is a pioneering field in the application of machine learning models. Interestingly, this essential domain, once one of the most resistant to adopting new information technologies, is now at the forefront of machine learning applications.

This course aims to assist in our adaptation to the AI era in healthcare. It covers basic machine learning models and advanced applications in real-world healthcare practices, with a special emphasis on the public health domain. As an introductory course, it is designed for researchers in the broad field of healthcare. Given its nature as a summer course, it requires a minimal level of programming. The focus will be on 1) developing an intuitive understanding of machine learning models; 2) showcasing interesting use cases of both basic and complex machine learning models; 3) presenting real-world implementations of machine learning models in healthcare practices.

Each session of the course consists of a lecture (occupying the majority of the time) and an academic discussion on the use of machine learning models in practical applications (dependent on the remaining time).

After completing this five-day course, students are expected to acquire a fundamental technical understanding of common machine learning models and a comprehensive knowledge of their applications in the healthcare field.

Required textbook: not needed