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Transferring deep convolutional network representations from SPECT to improve PET cardiac outcome prediction.

, , , , , , , , , , , , , and . Medical Imaging: Image Processing, volume 12464 of SPIE Proceedings, SPIE, (2023)

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Handling missing values in machine learning to predict patient-specific risk of adverse cardiac events: Insights from REFINE SPECT registry., , , , , , , , , and 10 other author(s). Comput. Biol. Medicine, (2022)Transferring deep convolutional network representations from SPECT to improve PET cardiac outcome prediction., , , , , , , , , and 4 other author(s). Medical Imaging: Image Processing, volume 12464 of SPIE Proceedings, SPIE, (2023)Time and event-specific deep learning for personalized risk assessment after cardiac perfusion imaging., , , , , , , , , and 11 other author(s). npj Digit. Medicine, (2023)ACCF/ASNC/ACR/AHA/ASE/SCCT/SCMR/SNM 2009 Appropriate Use Criteria for Cardiac Radionuclide Imaging. A Report of the American College of Cardiology Foundation Appropriate Use Criteria Task Force, the American Society of Nuclear Cardiology, the American College of Radiology, the American Heart Association, the American Society of Echocardiography, the Society of Cardiovascular Computed Tomography, the Society for Cardiovascular Magnetic Resonance, and the Society of Nuclear Medicine, , , , , , , and . Circulation, (2009)