Connection

Carlo De Cecco to Severity of Illness Index

This is a "connection" page, showing publications Carlo De Cecco has written about Severity of Illness Index.
Connection Strength

0.671
  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: 0.107
  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: 0.095
  3. Toward understanding COVID-19 pneumonia: a deep-learning-based approach for severity analysis and monitoring the disease. Sci Rep. 2021 05 27; 11(1):11112.
    View in: PubMed
    Score: 0.032
  4. 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: 0.030
  5. Ischemia and outcome prediction by cardiac CT based machine learning. Int J Cardiovasc Imaging. 2020 Dec; 36(12):2429-2439.
    View in: PubMed
    Score: 0.030
  6. 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: 0.029
  7. 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: 0.028
  8. 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: 0.028
  9. 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: 0.028
  10. 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: 0.026
  11. 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: 0.025
  12. 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: 0.025
  13. 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: 0.024
  14. 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: 0.024
  15. 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: 0.023
  16. 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: 0.023
  17. 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: 0.023
  18. 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: 0.022
  19. MDCT classification of steatotic liver: a multicentric analysis. Eur J Gastroenterol Hepatol. 2015 Mar; 27(3):290-7.
    View in: PubMed
    Score: 0.021
  20. Morphological and functional evaluation of intrapericardial cyst as a cause of severe right heart failure: dual source computed tomography and magnetic resonance imaging. J Cardiovasc Med (Hagerstown). 2009 Apr; 10(4):363-4.
    View in: PubMed
    Score: 0.014
  21. Incidental dual source computed tomography imaging of ductal aortic coarctation, left subclavian artery stenosis and bicuspid aortic valve in a patient admitted for atypical chest pain. Interact Cardiovasc Thorac Surg. 2008 May; 7(3):504-5.
    View in: PubMed
    Score: 0.013
Connection Strength

The connection strength for concepts is the sum of the scores for each matching publication.

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