Connection

Carlo De Cecco to Predictive Value of Tests

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This is a "connection" page, showing publications Carlo De Cecco has written about Predictive Value of Tests.
Carlo De Cecco
Connection Strength
1.193
Predictive Value of Tests
  1. Artificial intelligence machine learning-based coronary CT fractional flow reserve (CT-FFRML): Impact of iterative and filtered back projection reconstruction techniques. J Cardiovasc Comput Tomogr. 2019 Nov - Dec; 13(6):331-335.
    View in: PubMed
    Score: 0.120
  2. Global quantification of left ventricular myocardial perfusion at dynamic CT imaging: Prognostic value. J Cardiovasc Comput Tomogr. 2017 Jan - Feb; 11(1):16-24.
    View in: PubMed
    Score: 0.106
  3. Sub-acute intramural haematoma of the ascending aorta. Interact Cardiovasc Thorac Surg. 2010 Nov; 11(5):701-2.
    View in: PubMed
    Score: 0.068
  4. Discordance Between Coronary Artery Calcium Area and Density Predicts Long-Term Atherosclerotic Cardiovascular Disease Risk. JACC Cardiovasc Imaging. 2022 Nov; 15(11):1929-1940.
    View in: PubMed
    Score: 0.039
  5. Evolving Role of Calcium Density in Coronary Artery Calcium Scoring and?Atherosclerotic Cardiovascular Disease Risk. JACC Cardiovasc Imaging. 2022 09; 15(9):1648-1662.
    View in: PubMed
    Score: 0.038
  6. The Journal of cardiovascular computed tomography: A year in review 2021. J Cardiovasc Comput Tomogr. 2022 May-Jun; 16(3):266-276.
    View in: PubMed
    Score: 0.038
  7. CarDiac magnEtic Resonance for prophylactic Implantable-cardioVerter defibrillAtor ThErapy in Non-Ischaemic dilated CardioMyopathy: an international Registry. Europace. 2021 07 18; 23(7):1072-1083.
    View in: PubMed
    Score: 0.036
  8. Predictive Value of Cardiac CTA, Cardiac MRI, and Transthoracic Echocardiography for Cardioembolic Stroke Recurrence. AJR Am J Roentgenol. 2021 08; 217(2):336-346.
    View in: PubMed
    Score: 0.036
  9. Differences in coronary vasodilatory capacity and atherosclerosis in endurance athletes using coronary CTA and computational fluid dynamics (CFD): Comparison with a sedentary lifestyle. Eur J Radiol. 2020 Sep; 130:109168.
    View in: PubMed
    Score: 0.034
  10. Ischemia and outcome prediction by cardiac CT based machine learning. Int J Cardiovasc Imaging. 2020 Dec; 36(12):2429-2439.
    View in: PubMed
    Score: 0.034
  11. Rationale and design of the quantification of myocardial blood flow using dynamic PET/CTA-fused imagery (DEMYSTIFY) to determine physiological significance of specific coronary lesions. J Nucl Cardiol. 2020 06; 27(3):1030-1039.
    View in: PubMed
    Score: 0.033
  12. The Journal of Cardiovascular Computed Tomography year in review - 2019. J Cardiovasc Comput Tomogr. 2020 Mar - Apr; 14(2):107-117.
    View in: PubMed
    Score: 0.033
  13. Performance of a deep learning algorithm for the evaluation of CAD-RADS classification with CCTA. Atherosclerosis. 2020 02; 294:25-32.
    View in: PubMed
    Score: 0.033
  14. Influence of Coronary Calcium on Diagnostic Performance of Machine Learning CT-FFR: Results From MACHINE Registry. JACC Cardiovasc Imaging. 2020 03; 13(3):760-770.
    View in: PubMed
    Score: 0.032
  15. Advanced atherosclerosis imaging by CT: Radiomics, machine learning and deep learning. J Cardiovasc Comput Tomogr. 2019 Sep - Oct; 13(5):274-280.
    View in: PubMed
    Score: 0.031
  16. Prognostic value of CT myocardial perfusion imaging and CT-derived fractional flow reserve for major adverse cardiac events in patients with coronary artery disease. J Cardiovasc Comput Tomogr. 2019 May - Jun; 13(3):26-33.
    View in: PubMed
    Score: 0.031
  17. Progression of coronary atherosclerotic plaque burden and relationship with adverse cardiovascular event in asymptomatic diabetic patients. BMC Cardiovasc Disord. 2019 02 11; 19(1):39.
    View in: PubMed
    Score: 0.031
  18. Feasibility of extracellular volume quantification using dual-energy CT. J Cardiovasc Comput Tomogr. 2019 Jan - Feb; 13(1):81-84.
    View in: PubMed
    Score: 0.030
  19. Machine learning in cardiac CT: Basic concepts and contemporary data. J Cardiovasc Comput Tomogr. 2018 May - Jun; 12(3):192-201.
    View in: PubMed
    Score: 0.029
  20. Coronary CT Angiography-derived Fractional Flow Reserve: Machine Learning Algorithm versus Computational Fluid Dynamics Modeling. Radiology. 2018 Jul; 288(1):64-72.
    View in: PubMed
    Score: 0.029
  21. Quantitative inversion time prescription for myocardial late gadolinium enhancement using T1-mapping-based synthetic inversion recovery imaging: reducing subjectivity in the estimation of inversion time. Int J Cardiovasc Imaging. 2018 Jun; 34(6):921-929.
    View in: PubMed
    Score: 0.028
  22. Iterative beam-hardening correction with advanced modeled iterative reconstruction in low voltage CT coronary calcium scoring with tin filtration: Impact on coronary artery calcium quantification and image quality. J Cardiovasc Comput Tomogr. 2017 Sep - Oct; 11(5):354-359.
    View in: PubMed
    Score: 0.028
  23. CT angiography to evaluate coronary artery disease and revascularization requirement before trans-catheter aortic valve replacement. J Cardiovasc Comput Tomogr. 2017 Sep - Oct; 11(5):338-346.
    View in: PubMed
    Score: 0.027
  24. Accuracy of Noncontrast Quiescent-Interval Single-Shot Lower Extremity MR Angiography Versus CT?Angiography for Diagnosis of Peripheral Artery Disease: Comparison With Digital Subtraction Angiography. JACC Cardiovasc Imaging. 2017 10; 10(10 Pt A):1116-1124.
    View in: PubMed
    Score: 0.027
  25. Cardiac CTA for Evaluation of Prosthetic?Valve?Dysfunction. JACC Cardiovasc Imaging. 2017 01; 10(1):91-93.
    View in: PubMed
    Score: 0.026
  26. Correlation and predictive value of aortic root calcification markers with coronary artery calcification and obstructive coronary artery disease. Radiol Med. 2017 Feb; 122(2):113-120.
    View in: PubMed
    Score: 0.026
  27. Prognostic implications of coronary CT angiography-derived quantitative markers for the prediction of major adverse cardiac events. J Cardiovasc Comput Tomogr. 2016 Nov - Dec; 10(6):458-465.
    View in: PubMed
    Score: 0.026
  28. Coronary CT angiography-derived quantitative markers for predicting in-stent restenosis. J Cardiovasc Comput Tomogr. 2016 Sep-Oct; 10(5):377-83.
    View in: PubMed
    Score: 0.026
  29. Dynamic CT myocardial perfusion imaging identifies early perfusion abnormalities in diabetes and hypertension: Insights from a multicenter registry. J Cardiovasc Comput Tomogr. 2016 Jul-Aug; 10(4):301-8.
    View in: PubMed
    Score: 0.025
  30. Coronary CT angiography derived morphological and functional quantitative plaque markers correlated with invasive fractional flow reserve for detecting hemodynamically significant stenosis. J Cardiovasc Comput Tomogr. 2016 May-Jun; 10(3):199-206.
    View in: PubMed
    Score: 0.025
  31. Mammographic detection of breast arterial calcification as an independent predictor of coronary atherosclerotic disease in a single ethnic cohort of African American women. Atherosclerosis. 2015 Sep; 242(1):218-21.
    View in: PubMed
    Score: 0.024
  32. Diagnostic confidence of computed tomography and magnetic resonance in focal liver pathology. Eur J Gastroenterol Hepatol. 2015 Jan; 27(1):97-101.
    View in: PubMed
    Score: 0.023
  33. Correlation of cardiac magnetic resonance imaging and histopathology in eosinophilic endomyocarditis. Circ Cardiovasc Imaging. 2015 Jan; 8(1).
    View in: PubMed
    Score: 0.023
Connection Strength

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