HST.953 is a course about the practical considerations for operationalizing machine learning in healthcare settings. We begin the course with a focus on robust, private and fair machine learning (ML) using real retrospective healthcare data. We follow this with experiences in visualization (VIS) that target utility and clinical value. Finally, we explore the intermediate “implementation science” (IMP) tying together how real models might be potentially used through a visual system by practicing clinical staff.

ACKNOWLEDGEMENTS

Rodrigo Gameiro assisted with organizataion of course materials for publication on MIT OpenCourseWare.