Connection

Carlo De Cecco to Fractional Flow Reserve, Myocardial

This is a "connection" page, showing publications Carlo De Cecco has written about Fractional Flow Reserve, Myocardial.
  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: 0.566
  2. 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: 0.159
  3. 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: 0.150
  4. Impact of Coronary Computerized Tomography Angiography-Derived Plaque Quantification and Machine-Learning Computerized Tomography Fractional Flow Reserve on Adverse Cardiac Outcome. Am J Cardiol. 2019 11 01; 124(9):1340-1348.
    View in: PubMed
    Score: 0.150
  5. 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: 0.145
  6. Coronary CT angiography-derived plaque quantification with artificial intelligence CT fractional flow reserve for the identification of lesion-specific ischemia. Eur Radiol. 2019 May; 29(5):2378-2387.
    View in: PubMed
    Score: 0.143
  7. 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: 0.136
  8. Noninvasive Derivation of Fractional Flow Reserve From Coronary Computed Tomographic Angiography: A Review. J Thorac Imaging. 2018 Mar; 33(2):88-96.
    View in: PubMed
    Score: 0.135
  9. Coronary CT Angiography-derived Fractional Flow Reserve. Radiology. 2017 10; 285(1):17-33.
    View in: PubMed
    Score: 0.132
  10. Coronary Computed Tomographic Angiography-Derived Fractional Flow Reserve for Therapeutic Decision Making. Am J Cardiol. 2017 Dec 15; 120(12):2121-2127.
    View in: PubMed
    Score: 0.131
  11. Coronary Computed Tomographic Angiography-Derived Fractional Flow Reserve Based on Machine Learning for Risk Stratification of Non-Culprit Coronary Narrowings in Patients with Acute Coronary Syndrome. Am J Cardiol. 2017 Oct 15; 120(8):1260-1266.
    View in: PubMed
    Score: 0.130
  12. 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: 0.118
  13. Diagnostic value of quantitative stenosis predictors with coronary CT angiography compared to invasive fractional flow reserve. Eur J Radiol. 2015 Aug; 84(8):1509-1515.
    View in: PubMed
    Score: 0.111
  14. Artificial Intelligence in Coronary Computed Tomography Angiography: From Anatomy to Prognosis. Biomed Res Int. 2020; 2020:6649410.
    View in: PubMed
    Score: 0.041
  15. 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: 0.039
  16. Gender differences in the diagnostic performance of machine learning coronary CT angiography-derived fractional flow reserve -results from the MACHINE registry. Eur J Radiol. 2019 Oct; 119:108657.
    View in: PubMed
    Score: 0.038
Connection Strength

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Publication scores are based on many factors, including how long ago they were written and whether the person is a first or senior author.