Teaching

APPLY. COMPUTE. ENGINEER. 

ACE the COM-IN Curriculum. Be a part of the healthcare revolution!

BME | SIE 477/577 

 Introduction to Biomedical Informatics

bme477

Course Overview: (3 credits) Driven by efforts to improve human health and healthcare systems, this course will cover relevant topics at the intersection of people, information, and technology. Specifically, we will survey the field of biomedical informatics that studies the effective uses of biomedical data, information, and knowledge from molecules and cellular processes to individuals and populations, for scientific inquiry, problem solving, and decision making. We will explore foundations and methods from both biomedical and computing perspectives, including hands-on experiences with systems, tools, and technologies in the health system.

Audience: Undergraduate students, fellows (including clinicians), graduate students, and scientists from all fields with interest in either biomedical and healthcare applications or computing are welcome to enroll in this course.

Term: Offered in Fall.

BME | SIE 578  

 Artificial Intelligence for Health and Medicine

AI4HAM

Course Overview: (3 credits) The practice of modern medicine in a highly regulated, complex, sociotechnical enterprise is a testament to the future healthcare system where the balance between human intelligence and artificial expertise will be at stake. The goal of this course is to introduce the underlying concepts, methods, and the potential of intelligent systems in medicine. We will explore foundational methods in artificial intelligence (AI) with greater emphasis on machine learning and knowledge representation and reasoning, and apply them to specific areas in medicine and healthcare including, but not limited to, clinical risk stratification, phenotype and biomarker discovery, time series analysis of physiological data, disease progression modeling, and patient outcome prediction. As a research and project-based course, student(s) will have opportunities to identify and specialize in particular AI methods, clinical/healthcare applications, and relevant tools.

Audience: Graduate students in biomedical, systems, and computer engineering, computer science, information science, statistics, and applied math.

Term: Offered in Spring.

BME 376  

 Biomedical Statistics

bmestat

Course Overview: (3 credits) This course covers application of statistics to biomedical engineering and research. Topics include describing and summarizing biomedical data, study designs, probability distributions, diagnostic testing, and statistical inference for biomedical applications. All topics will involve use of R Statistical Computing Software.  

Audience: Undergraduate students in biomedical engineering, physiology, and health sciences.

Term: Offered in Fall.