Non-invasive detection of cardiac allograft rejection among heart transplant recipients using an electrocardiogram based deep learning model
Demilade Adedinsewo(Jacksonville College), Mohamad H. Yamani(Jacksonville College), Tathagat Narula(Mayo Clinic in Florida), Rohan Goswami(Mayo Clinic in Florida), Heather D Hardway(Mayo Clinic in Florida), Paul A. Friedman(Mayo Clinic), Atta Behfar(Mayo Clinic), Rickey E. Carter(Mayo Clinic in Florida), Reza Arsanjani(WinnMed), Peter A. Noseworthy(WinnMed), Zachi I. Attia(Mayo Clinic in Arizona), Andrea Carolina Morales-Lara(WinnMed), Raouf E. Nakhleh(WinnMed), Juan Carlos Leoni-Moreno(Mayo Clinic in Florida), Mikolaj A. Wieczorek(Mayo Clinic in Florida), Patrick W. Johnson(Mayo Clinic in Florida), Parag C. Patel(Mayo Clinic in Florida), Erika J. Douglass(Mayo Clinic in Florida), Melissa Lyle(Mayo Clinic in Florida), Brian Hardaway(WinnMed), Alexander Heckman(Jackson Memorial Hospital), Bryan Dangott(WinnMed), D. Eric Steidley(WinnMed), Mohsin Abbas(Mayo Clinic in Arizona), Francisco López-Jiménez(Mayo Clinic in Arizona)
Cited by 23
Related Papers
Screening for cardiac contractile dysfunction using an artificial intelligence–enabled electrocardiogram
|Nature Medicine|2018|1.3k
Convalescent Plasma Antibody Levels and the Risk of Death from Covid-19
|New England Journal of Medicine|2021|553
Cardiopoietic Stem Cell Therapy in Heart Failure
|Journal of the American College of Cardiology|2013|485
Early safety indicators of COVID-19 convalescent plasma in 5000 patients
|Journal of Clinical Investigation|2020|485
Effect of Adherence to Oral Anticoagulants on Risk of Stroke and Major Bleeding Among Patients With Atrial Fibrillation
|Journal of the American Heart Association|2016|450