Advancing Healthcare through Robotics and Machine Learning

Advancing Healthcare through Robotics and Machine Learning

Advancing Healthcare through Robotics and Machine Learning

One of the biggest dangers for trauma patients during the ambulance ride is undiagnosed, internal hemorrhagic bleeding. It’s currently undetectable with methods available on the ambulance ride. You can’t see it … but a robot can.

Axel Krieger—an assistant professor of mechanical engineering at the University of Maryland’s A. James Clark School of Engineering who specializes in medical robotics and computer vision—says that estimates suggest one-third of trauma fatalities likely would have survived if they had access to hospital-level of care sooner. He aims to help make that level of care standard on the way to the hospital by equipping ambulances with a medical robot enhanced by machine learning.

Watch the video above to learn more.

Dr. Krieger is a member of the Maryland Robotics Center.

Are you are a member of the media interested in connecting with a robotics engineer at the University of Maryland? Please email: clark-communications@umd.edu 

Related Articles:
Machine Learning's Translational Medicine
The Battery Revolution
Algorithms and Autonomous Discovery
The Buddy System: Human-Computer Teams
Manocha Receives 2022 Verisk AI Faculty Research Award
Measuring Change in the Atmosphere
UMD Study Compares AI Models for HVAC Systems, Highlighting Performance and Efficiency Differences
Tuna-Inspired Mechanical Fin Could Boost Underwater Drone Power
Developing Efficient Systems for Deep Sea Exploration
Inspired by Nature, Researchers Improve System Movement

September 17, 2019


Prev   Next

Current Headlines

Stroka Appointed Associate Chair for Undergraduate Studies and Director of Undergraduate Programs

New Oxyhalide Electrolyte Breaks Barriers for Solid-State Battery Performance

International Research Exchange Spotlight

Md Mehrab Hossen Siam Receives Graduate Endowed Fellowship

New Initiatives Push Toward Safe & Reliable Autonomous Systems

Led by Professor Mohammad Hafezi, Researchers Identify Groovy Way to Beat Diffraction Limit

Shaping the Future of Engineering: How Maryland Is Leading in AI Education and Research

UMD-Led Team Wins Major NSF Grant to Pioneer “High-Entropy” Quantum Materials

News Resources

Return to Newsroom

Search News

Archived News

Events Resources

Events Calendar