Ulysses G. J. Balis, M.D., FCAP, FASCP

Artificial intelligence (AI) has the potential to revolutionize healthcare, but integrating AI-based techniques into routine medical practice has proven to be a significant challenge. A plenary session at the virtual 2020 AACC Annual Scientific Meeting & Clinical Lab Expo will explore how one clinical lab overcame this challenge to implement a machine learning-based test, while a second session will take a big picture look at what machine learning is and how it could transform medicine.

Machine learning is a type of AI that uses statistics to find patterns in massive amounts of data. It could launch healthcare into a new era by mining medical data to find cures for diseases, identify vulnerable patients before they become ill, and better personalize testing and treatments. In spite of this technology’s promise, though, the medical community continues to grapple with numerous barriers to adoption, and in the field of laboratory medicine in particular, very few machine learning tests are currently offered as part of regular care.

A 10-year machine learning project undertaken by Ulysses G.J. Balis, MD, and his colleagues at the University of Michigan in Ann Arbor could help to change this by providing a blueprint for other healthcare institutions looking to harness AI… Continue reading.

WASHINGTON, D.C.— The American Institute for Medical and Biological Engineering (AIMBE) has announced the pending induction of Ulysses G. J. Balis, M.D., FCAP, FASCP, Professor of Pathology; Director, Division of Pathology Informatics; Director, Pathology Informatics Fellowship Program, Division of Pathology Informatics, Department of Pathology, University of Michigan, to its College of Fellows. Dr. Balis was nominated, reviewed, and elected by peers and members of the College of Fellows For outstanding contributions to the fields of laboratory instrumentation, pathology bioinformatics and computational imaging in histology image search/analysis.