Cornell Research Group Explores Potential of Machine Learning in Medicine

Medicine and artificial intelligence are ever-evolving fields at the forefront of scientific discovery. A new Cornell research group — Machine Learning in Medicine — aims to coalesce the two, with the goal of improving methods for disease detection and diagnosis. This endeavor is a collaboration between faculty at Cornell Tech and Weill Cornell Medicine, bringing together “researchers with common interests and complementary expertise.” MLIM’s work is primarily an interdisciplinary dialogue, bridging campuses and research fields. 

“The idea was to link people with a machine learning background in Ithaca to [people working with] clinical data and hypotheses at Weill,” said Prof. Amy Kuceyeski, mathematics and radiology, one of the organizing members of the group. While Kuceyeski’s background is in mathematics, she started learning methods for modeling biological systems as a postdoctoral researcher at Weill. Seeing this as an area for innovation, Kuceyeski helped establish MLIM in 2018.