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1. TAI-GAN: A Temporally and Anatomically Informed Generative Adversarial Network for early-to-late frame conversion in dynamic cardiac PET inter-frame motion correction

3. TAI-GAN: Temporally and Anatomically Informed GAN for early-to-late frame conversion in dynamic cardiac PET motion correction

8. Prevalence and significance of extracardiac uptake on pyrophosphate imaging in the SCAN-MP study: the first 379 cases

9. Data Management and Network Architecture Effect on Performance Variability in Direct Attenuation Correction via Deep Learning for Cardiac SPECT: A Feasibility Study

11. Diagnostic performance characteristics of planar quantitative and semi-quantitative parameters of Tc99m pyrophosphate (PYP) imaging for diagnosis of transthyretin (ATTR) cardiac amyloidosis: the SCAN-MP study

12. Handling missing values in machine learning to predict patient-specific risk of adverse cardiac events: Insights from REFINE SPECT registry

14. 18F-FDG PET/CT and Radiolabeled Leukocyte SPECT/CT Imaging for the Evaluation of Cardiovascular Infection in the Multimodality Context: ASNC Imaging Indications (ASNC I2) Series Expert Consensus Recommendations From ASNC, AATS, ACC, AHA, ASE, EANM, HRS, IDSA, SCCT, SNMMI, and STS

15. Time and event-specific deep learning for personalized risk assessment after cardiac perfusion imaging

16. Unsupervised learning to characterize patients with known coronary artery disease undergoing myocardial perfusion imaging

18. Direct Attenuation Correction Using Deep Learning for Cardiac SPECT: A Feasibility Study

19. Clinical phenotypes among patients with normal cardiac perfusion using unsupervised learning: a retrospective observational study

23. A phenomapping-derived tool to personalize the selection of anatomical vs. functional testing in evaluating chest pain (ASSIST).

24. Direct Image-Based Attenuation Correction using Conditional Generative Adversarial Network for SPECT Myocardial Perfusion Imaging.

30. Mitigating bias in deep learning for diagnosis of coronary artery disease from myocardial perfusion SPECT images

34. Comparison of diabetes to other prognostic predictors among patients referred for cardiac stress testing: A contemporary analysis from the REFINE SPECT Registry

36. Myocardial Ischemic Burden and Differences in Prognosis Among Patients With and Without Diabetes: Results From the Multicenter International REFINE SPECT Registry

37. Direct Risk Assessment From Myocardial Perfusion Imaging Using Explainable Deep Learning

41. Diagnostic safety of a machine learning-based automatic patient selection algorithm for stress-only myocardial perfusion SPECT

43. TAI-GAN: Temporally and Anatomically Informed GAN for Early-to-Late Frame Conversion in Dynamic Cardiac PET Motion Correction

45. Detection of Left Ventricular Systolic Dysfunction From Electrocardiographic Images

46. Unlocking Diversity in Cardiovascular Clinical Research: Lessons from the SCAN-MP (Screening for Cardiac Amyloidosis with Nuclear Imaging in Minority Populations) Study

47. TAI-GAN: A Temporally and Anatomically Informed Generative Adversarial Network for early-to-late frame conversion in dynamic cardiac PET inter-frame motion correction

49. Deep Learning Analysis of Upright-Supine High-Efficiency SPECT Myocardial Perfusion Imaging for Prediction of Obstructive Coronary Artery Disease: A Multicenter Study

50. Deep Learning for Prediction of Obstructive Disease From Fast Myocardial Perfusion SPECT A Multicenter Study

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