Machine Learning for Healthcare
6.S897 · Electrical Engineering and Computer Science, Health Sciences and Technology · Graduate · Spring 2019
Prof. Peter Szolovits, Prof. David Sontag
This course introduces students to machine learning in healthcare, including the nature of clinical data and the use of machine learning for risk stratification, disease progression modeling, precision medicine, diagnosis, subtype discovery, and improving clinical workflows.
The syllabus, on MIT OpenCourseWare
The full course — syllabus, assigned readings, problem sets, exams, and lecture notes — lives on OCW. These open the real thing:
Syllabus ↗
Course overview, grading, schedule
Readings ↗
The assigned reading list, session by session
Assignments ↗
Problem sets and projects
Full course on OCW ↗
Everything, including lecture materials
Attribution
Prof. Peter Szolovits, Prof. David Sontag. 6.S897 Machine Learning for Healthcare. Spring 2019. Massachusetts Institute of Technology: MIT OpenCourseWare, https://ocw.mit.edu. License: CC BY-NC-SA 4.0.
Course materials are © their authors and licensed CC BY-NC-SA 4.0. CurrMana links to the source and does not re-host them.