Connection

Carlo De Cecco to ROC Curve

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This is a "connection" page, showing publications Carlo De Cecco has written about ROC Curve.
Carlo De Cecco
Connection Strength
0.761
ROC Curve
  1. Diagnostic accuracy of low and high tube voltage coronary CT angiography using an X-ray tube potential-tailored contrast medium injection protocol. Eur Radiol. 2018 May; 28(5):2134-2142.
    View in: PubMed
    Score: 0.133
  2. Texture analysis as imaging biomarker of tumoral response to neoadjuvant chemoradiotherapy in rectal cancer patients studied with 3-T magnetic resonance. Invest Radiol. 2015 Apr; 50(4):239-45.
    View in: PubMed
    Score: 0.111
  3. Invited commentary. Ann Thorac Surg. 2008 Nov; 86(5):1553.
    View in: PubMed
    Score: 0.071
  4. 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
  5. 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: 0.037
  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: 0.036
  7. CT Attenuation Analysis of Carotid Intraplaque Hemorrhage. AJNR Am J Neuroradiol. 2018 Jan; 39(1):131-137.
    View in: PubMed
    Score: 0.033
  8. 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: 0.033
  9. 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: 0.033
  10. Diffusion-weighted magnetic resonance imaging in locally advanced rectal cancer treated with neoadjuvant chemoradiotherapy. Eur J Surg Oncol. 2017 Jul; 43(7):1324-1329.
    View in: PubMed
    Score: 0.032
  11. Coronary Computed Tomography Angiography-Derived Plaque Quantification in Patients With Acute Coronary?Syndrome. Am J Cardiol. 2017 03 01; 119(5):712-718.
    View in: PubMed
    Score: 0.031
  12. 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: 0.030
  13. 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: 0.030
  14. 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: 0.030
  15. 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: 0.028
  16. MDCT classification of steatotic liver: a multicentric analysis. Eur J Gastroenterol Hepatol. 2015 Mar; 27(3):290-7.
    View in: PubMed
    Score: 0.028
  17. 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: 0.027
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.