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Case Western Reserve University lab and partners using Artificial Intelligence to improve heart transplant outcomes

The AI is aimed at determining which cardiac patients will be more likely to accept or reject a new heart.
Credit: Case Western Reserve University

CLEVELAND — New Artificial Intelligence is being developed to increase success rates in heart transplant patients. And Cleveland is at the center of the research.

Bioengineer and scientist Anant Madabhushi, along with a team of biomedical researchers out of Case Western Reserve University and partners in the Perelman School of Medicine at University of Pennsylvania, Cleveland Clinic and Cedars-Sinai Medical Center have begun training computers to analyze pathology images and predict which patients will accept or reject heart transplants.

A National Institutes of Health grant of $3.2 million was recently awarded to the team to pursue the project.

"Right now, the pathologists look at the biopsies and use their own rating scheme based on features of the heart tissue," said Madabhushi, the F. Alex Nason Professor II of Biomedical Engineering at Case Western Reserve. "What we're doing, is applying the power of AI and computer vision to analyze the biopsy tissue images to quantitatively and reproducibly distinguish different cardiac rejection grades."

Madabhushi and his team of researches, which includes over 60 post-doctoral students, graduate students and undergraduates, have successfully taught the AI computers to find variations, that would otherwise mostly be invisible to the naked eye, among thousands of images of numerous types of cancer.

"Those variations in cellular arrangement and appearance, when interpreted by algorithms developed by the researches, have helped scientists in previous studies more accurately predict which patients will respond better to chemotherapy or immunotherapy, for example, or to identify differences in how cancer cells appear among racial groups, among other findings," a press release from Case Western reads.

In addition, researchers plant to develop long-term predictions of patient success, compare AI performance results to human pathologists, and better define the molecular biology of heart tissues. 

Other collaborators on the project include Drs. Michael D. Feldman, Priti Lal and Eliot Peyster from Penn; Dr. Wilson Tang from Cleveland Clinic, Dr. Jon Kobashigawa at Cedars-Sinai; professor Pingfu Fu, research assistant professor Andrew Janowczyk and graduate student Sara Arabyarmohammadi from the Case Western Reserve team.

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