HST.953 Collaborative Data Science in Medicine
A guide for data scientists, engineers, and clinicians who are interested in performing retrospective research using data from electronic health records. Instruction provided in clinical decision-making and secondary use of clinical data, using the Medical Information Mart for Intensive Care (MIMIC) database and the eICU Collaborative Research Database. Covers steps in parsing a clinical question into a study design and methodology for data analysis and interpretation. Activities include review of case studies using the MIMIC and the eICU Collaborative Research Database and a team project. Student teams choose a question and clinician to work with for their project. Teams meet weekly with clinicians at the hospitals at arranged time.
This class has no prerequisites.
This class counts for a total of 12 credits. This is a graduate-level class.
You can find more information at the http://www.google.com/search?&q=MIT+%2B+HST.953&btnG=Google+Search&inurl=https site.
© Copyright 2015 Yasyf Mohamedali