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Organization, Regulations, and Courses 2023-24

COSC 89.28 Transforming Healthcare through Machine Learning: Challenges and Opportunities

Machine Learning (ML) lies at the core of a wide range of healthcare applications spanning from diagnosis to delivery of care. This course gives an overview of challenges and opportunities for ML in the era of digital health. We will explore advanced ML methods for healthcare and medicine through research papers. Specifically, we will cover recent successes of natural language processing, time-series analysis, and transfer learning to advance healthcare research. Students will choose and complete a course project, write a project report, and make project presentations at the end of the course. The course also requires the students to analyze, present, and discuss research papers.

The course is open to graduate and ambitious undergraduate students who are interested to gain hands-on experience in applied ML research. The course is designed to enable students to improve their technical communication and review skills and explore new research directions. It is important to note that this course will be conducted like a seminar (i.e. there are no formal lectures). We assume students are willing and able to learn some necessary background materials on their own. There will be office hours outside of scheduled class lectures.

The Timetable of Class Meetings contains the most up-to-date information about a course. It includes not only the meeting time and instructor, but also its official distributive and/or world culture designation. This information supersedes any information you may see elsewhere, to include what may appear in this ORC/Catalog or on a department/program website. Note that course attributes may change term to term therefore those in effect are those (only) during the term in which you enroll in the course.