Direct Risk Assessment From Myocardial Perfusion Imaging Using Explainable Deep Learning

This publication has 33 references indexed in Scilit:

• Prognostic Value of Combined Clinical and Myocardial Perfusion Imaging Data Using Machine Learning
  JACC: Cardiovascular Imaging, 2018
• Prognostic Value of Coronary Artery Calcium Scoring in Addition to Single-Photon Emission Computed Tomographic Myocardial Perfusion Imaging in Symptomatic Patients
  Circulation: Cardiovascular Imaging, 2016
• Calibration of Risk Prediction Models
  Medical Decision Making, 2014
• Multiple opportunities to reduce radiation dose from myocardial perfusion imaging
  European Journal of Nuclear Medicine and Molecular Imaging, 2013
• 2012 ACCF/AHA/ACP/AATS/PCNA/SCAI/STS Guideline for the Diagnosis and Management of Patients With Stable Ischemic Heart Disease
  JACC, 2012
• Prediction error estimation: a comparison of resampling methods
  Bioinformatics, 2005
• Automated quantification of myocardial perfusion SPECT using simplified normal limits
  Journal of Nuclear Cardiology, 2005
• Comparison of the Short-Term Survival Benefit Associated With Revascularization Compared With Medical Therapy in Patients With No Prior Coronary Artery Disease Undergoing Stress Myocardial Perfusion Single Photon Emission Computed Tomography
  Circulation, 2003
• Standardized Myocardial Segmentation and Nomenclature for Tomographic Imaging of the Heart
  Circulation, 2002
• Comparing the Areas under Two or More Correlated Receiver Operating Characteristic Curves: A Nonparametric Approach
  Biometrics, 1988