Every day, people from all over the world use digital devices to generate large amounts of text, image, video, and biological data. Researchers typically use machine learning algorithms to process these large datasets to identify patterns that could inform decisions about our health. In this course, we will study how researchers and institutions are using machine learning for public health purposes. Can your digital footprints be used to predict when you will die? Can machine learning algorithms determine the quality of care you receive at a hospital? Can your interactions with a social media platform indicate whether you have insomnia? These and similar questions will be explored in this course using real world examples and data. We will also learn how bias imbedded in the data (e.g., due to a lack of representation of certain populations) and algorithms can worsen existing health inequalities. Students will be introduced to machine learning algorithms in R and have many opportunities to apply these algorithms to various datasets. Students are required to have some familiarity with R but are not expected to be experts. Please reach out to Dr. Nsoesie at onelaine@bu.edu, if you have any questions.

Note that this information may change at any time. Please visit the MyBU Student Portal for the most up-to-date course information.