Connection

Akos Varga-Szemes to Severity of Illness Index

This is a "connection" page, showing publications Akos Varga-Szemes has written about Severity of Illness Index.
Connection Strength

0.703
  1. Computed tomographic assessment of right ventricular long axis strain for prognosis after transcatheter aortic valve replacement. Eur J Radiol. 2022 Apr; 149:110212.
    View in: PubMed
    Score: 0.132
  2. Coronary plaque assessment of Vasodilative capacity by CT angiography effectively estimates fractional flow reserve. Int J Cardiol. 2021 05 15; 331:307-315.
    View in: PubMed
    Score: 0.123
  3. 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: 0.093
  4. Artificial Intelligence-based Fully Automated Per Lobe Segmentation and Emphysema-quantification Based on Chest Computed Tomography Compared With Global Initiative for Chronic Obstructive Lung Disease Severity of Smokers. J Thorac Imaging. 2020 May; 35 Suppl 1:S28-S34.
    View in: PubMed
    Score: 0.029
  5. Low-kV coronary artery calcium scoring with tin filtration using a kV-independent reconstruction algorithm. J Cardiovasc Comput Tomogr. 2020 May - Jun; 14(3):246-250.
    View in: PubMed
    Score: 0.028
  6. Evaluation of a Deep Learning-Based Automated CT Coronary Artery Calcium Scoring Algorithm. JACC Cardiovasc Imaging. 2020 02; 13(2 Pt 1):524-526.
    View in: PubMed
    Score: 0.028
  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. Automated plaque analysis for the prognostication of major adverse cardiac events. Eur J Radiol. 2019 Jul; 116:76-83.
    View in: PubMed
    Score: 0.027
  10. 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: 0.026
  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: 0.024
  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: 0.024
  13. Analysis of myocardial perfusion parameters in an ex-vivo porcine heart model using third generation dual-source CT. J Cardiovasc Comput Tomogr. 2017 Mar - Apr; 11(2):141-147.
    View in: PubMed
    Score: 0.023
  14. 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
  15. 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: 0.022
  16. 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: 0.022
  17. 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
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.