Biomedical Artificial Intelligence & Computation

To expedite research by simulating and investigating the behavior of complex systems using mathematics, physics and computer science.

Technologies

• Multiscale modeling from the molecular level to whole organ scale
• Biochemical models of metabolism
• Virtual physiological models of organs and vasculature
• Using AI to identify disease trends and health patterns

Applications

• Cellular and physiological metabolism simulation (Nagrath, Jensen, Chandrasekaran)
• Blood flow simulation (Nordsletten, Figueroa)
• Flow of liquid medication in human lungs (Grotberg)
• Simulation of drug delivery, surgery and treatment (Grotberg, Chandrasekaran, Figueroa, Nordsletten)
• Infectious diseases and Immunology (Arnold, Chandrasekaran, Jensen)
• Biophysical simulations of cells and proteins (Sept)
• Neural Imaging and Engineering (Liu, Draelos, Lempka)

Courses Offered

• BIOMEDE 350 Intro to BME Design
• BIOMEDE 487 AI in BME
• BIOMEDE 517 Neural Engineering
• BIOMEDE 599 Comp Tools for Genomic Technologies

The Healing Power of Big Data

The University of Michigan Health system serves 2.1 million patients a year, generating a tremendous amount of data that can reveal hidden trends and health patterns. With the university’s computational resources, we can model tissue structure and function from the molecular to the whole-organ scale to better understand things like the flow of ions in cells, blood in arteries, and air in the lungs.

Michigan’s Advanced Research Computing — Technology Services external link provides U-M researchers with advanced computing resources, including:

• A shared computing cluster, Flux, with more than 16,000 cores
• A Hadoop cluster for data-science research
• Cloud computing services
• Regional and national high performance computing and network resources