DSC
510:
Health Data Science
This course focuses on how data science can be used in modern healthcare, including for clinical studies and public health. Students will be introduced to a variety of healthcare data, such as electronic health records, payor data, genetic data, geospatial data, public health data, medical imaging, unstructured clinical notes, etc. The class will discuss a variety of data science techniques to analyze and understand patterns in such data, including machine learning and other modeling techniques, as well as effectively communicating those results back to clinicians and patients. Topics in the course will include healthcare-specific applications of the following: machine learning, data engineering, data visualization, computer vision, natural language processing (NLP), and human-computer interaction (HCI). We will also cover fundamental data concepts in health, health data ethics, and the history of health data science. The overarching aim of the course is for students to learn how to solve data science problems in the health sector.
DSC 441 or HIT 421 is a prerequisite for this course.
Spring 2024-2025
-
Section:
901
-
Class number:
33272
-
Meeting time:
Th
5:45PM
-
9:00PM
-
Location:
LEWIS 01208
at
Loop Campus
-
Instructor:
Casey Bennett
| View syllabus
Winter 2024-2025
-
Section:
801
-
Class number:
25022
-
Meeting time:
Th
5:45PM
-
9:00PM
-
Location:
LEWIS 01508
at
Loop Campus
-
Instructor:
Casey Bennett
| View syllabus
CLOSED
Spring 2023-2024
-
Section:
901
-
Class number:
33346
-
Meeting time:
Th
5:45PM
-
9:00PM
-
Location:
LEWIS 01208
at
Loop Campus
-
Instructor:
Casey Bennett
| View syllabus