| P50 | author | Daniel S Berman | Q89697826 |
| P2093 | author name string | Yuan Xu | |
| | Reza Arsanjani | |
| | Damini Dey | |
| | Guido Germano | |
| | Piotr J Slomka | |
| | Mathews Fish | |
| | Sean Hayes | |
| | Aryeh Shalev | |
| | Rine Nakanishi | |
| | Vishal Vahistha | |
| P2860 | cites work | Comparing the areas under two or more correlated receiver operating characteristic curves: a nonparametric approach | Q29614698 |
| | Boosting for tumor classification with gene expression data | Q30802288 |
| | Integration of clinical and imaging data to predict the presence of coronary artery disease with the use of neural networks | Q30970986 |
| | Standardized myocardial segmentation and nomenclature for tomographic imaging of the heart. A statement for healthcare professionals from the Cardiac Imaging Committee of the Council on Clinical Cardiology of the American Heart Association | Q34111674 |
| | Combined quantitative analysis of attenuation corrected and non-corrected myocardial perfusion SPECT: Method development and clinical validation | Q34112420 |
| | Improved quantification and normal limits for myocardial perfusion stress-rest change | Q34112453 |
| | Automated quality control for segmentation of myocardial perfusion SPECT. | Q34112498 |
| | ACC/AHA/ASNC guidelines for the clinical use of cardiac radionuclide imaging--executive summary: a report of the American College of Cardiology/American Heart Association Task Force on Practice Guidelines (ACC/AHA/ASNC Committee to Revise the 1995 G | Q34230607 |
| | Computational gene mapping to analyze continuous automated physiologic monitoring data in neuro-trauma intensive care | Q34357121 |
| | Myocardial perfusion scintigraphy: the evidence | Q35765832 |
| | Transient ischemic dilation for coronary artery disease in quantitative analysis of same-day sestamibi myocardial perfusion SPECT. | Q36039857 |
| | Comparison of fully automated computer analysis and visual scoring for detection of coronary artery disease from myocardial perfusion SPECT in a large population | Q36585799 |
| | Computational methods for DNA-binding protein and binding residue prediction | Q39616909 |
| | Transient ischemic dilation ratio of the left ventricle is a significant predictor of future cardiac events in patients with otherwise normal myocardial perfusion SPECT. | Q40546168 |
| | Analysis of Probability as an Aid in the Clinical Diagnosis of Coronary-Artery Disease | Q41582136 |
| | Structures of the recurrence plot of heart rate variability signal as a tool for predicting the onset of paroxysmal atrial fibrillation. | Q41894171 |
| | A Hyper-Solution Framework for SVM Classification: Application for Predicting Destabilizations in Chronic Heart Failure Patients. | Q42601421 |
| | Comparative prognostic value of automatic quantitative analysis versus semiquantitative visual analysis of exercise myocardial perfusion single-photon emission computed tomography | Q43772936 |
| | Adenosine myocardial perfusion single-photon emission computed tomography in women compared with men. Impact of diabetes mellitus on incremental prognostic value and effect on patient management | Q44392647 |
| | Prognostic implications of combined prone and supine acquisitions in patients with equivocal or abnormal supine myocardial perfusion SPECT | Q44608988 |
| | Automatic quantification of myocardial perfusion stress-rest change: a new measure of ischemia. | Q44762709 |
| | Identification of severe or extensive coronary artery disease in women by adenosine technetium-99m sestamibi SPECT. | Q46008570 |
| | Adenosine technetium-99m sestamibi myocardial perfusion SPECT in women: diagnostic efficacy in detection of coronary artery disease. | Q46347274 |
| | Combined supine and prone quantitative myocardial perfusion SPECT: method development and clinical validation in patients with no known coronary artery disease | Q46363421 |
| | Quantitative assessment of motion artifacts and validation of a new motion-correction program for myocardial perfusion SPECT. | Q46457063 |
| | Automatic quantification of ejection fraction from gated myocardial perfusion SPECT. | Q46496807 |
| | Quantitation in gated perfusion SPECT imaging: the Cedars-Sinai approach | Q46711287 |
| | Postischemic stunning can affect left ventricular ejection fraction and regional wall motion on post-stress gated sestamibi tomograms. | Q50921106 |
| | Simplified normal limits and automated quantitative assessment for attenuation-corrected myocardial perfusion SPECT. | Q51788143 |
| | Combined quantitative supine-prone myocardial perfusion SPECT improves detection of coronary artery disease and normalcy rates in women. | Q51923620 |
| | Improved classifications of myocardial bull's-eye scintigrams with computer-based decision support system. | Q52224930 |
| | Automatic reorientation of three-dimensional, transaxial myocardial perfusion SPECT images. | Q52339435 |
| | Computer-assisted diagnosis in the noninvasive evaluation of patients with suspected coronary artery disease | Q52708999 |
| | Interpretive reproducibility of stress Tc-99m sestamibi tomographic myocardial perfusion imaging. | Q52913332 |
| | Visual assessment of left ventricular perfusion and function with electrocardiography-gated SPECT has high intraobserver and interobserver reproducibility among experienced nuclear cardiologists and cardiology trainees. | Q52939947 |
| | Single photon-emission computed tomography. | Q53290097 |
| | Automated quantification of myocardial perfusion SPECT using simplified normal limits | Q62492869 |
| | Effectiveness of nuclear cardiology training guidelines: a comparison of trainees with experienced readers | Q71516078 |
| | Separate acquisition rest thallium-201/stress technetium-99m sestamibi dual-isotope myocardial perfusion single-photon emission computed tomography: a clinical validation study | Q72573690 |
| | Diagnostic performance of an expert system for the interpretation of myocardial perfusion SPECT studies | Q74306859 |
| P4510 | describes a project that uses | machine learning | Q2539 |
| P433 | issue | 4 | |
| P921 | main subject | coronary artery disease | Q844935 |
| | machine learning | Q2539 |
| P304 | page(s) | 553-562 | |
| P577 | publication date | 2013-05-24 | |
| P1433 | published in | Journal of Nuclear Cardiology | Q609415 |
| P1476 | title | Improved accuracy of myocardial perfusion SPECT for detection of coronary artery disease by machine learning in a large population | |
| P478 | volume | 20 | |