Below are the most recent publications written about "Coronary Stenosis" by people in Profiles.
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Varga-Szemes A, Schoepf UJ, Maurovich-Horvat P, Wang R, Xu L, Dargis DM, Emrich T, Buckler AJ. Coronary plaque assessment of Vasodilative capacity by CT angiography effectively estimates fractional flow reserve. Int J Cardiol. 2021 05 15; 331:307-315.
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van Assen M, Muscogiuri G, Caruso D, Lee SJ, Laghi A, De Cecco CN. Artificial intelligence in cardiac radiology. Radiol Med. 2020 Nov; 125(11):1186-1199.
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Tesche C, Bauer MJ, Baquet M, Hedels B, Straube F, Hartl S, Gray HN, Jochheim D, Aschauer T, Rogowski S, Schoepf UJ, Massberg S, Hoffmann E, Ebersberger U. Improved long-term prognostic value of coronary CT angiography-derived plaque measures and clinical parameters on adverse cardiac outcome using machine learning. Eur Radiol. 2021 Jan; 31(1):486-493.
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Feuchtner GM, Langer C, Senoner T, Barbieri F, Beyer C, Bonaros N, Schachner T, Friedrich G, Baldauf B, Taylor CA, Klauser A, Rauch S, Leipsic J, Dichtl W, Widmann G, De Cecco CN, Plank F. 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.
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Baumann S, Özdemir GH, Tesche C, Schoepf UJ, Golden JW, Becher T, Hirt M, Weiss C, Renker M, Akin I, Schoenberg SO, Borggrefe M, Haubenreisser H, Lossnitzer D, Overhoff D. Coronary CT angiography derived plaque markers correlated with invasive instantaneous flow reserve for detecting hemodynamically significant coronary stenoses. Eur J Radiol. 2020 Jan; 122:108744.
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Baumann S, Hirt M, Schoepf UJ, Rutsch M, Tesche C, Renker M, Golden JW, Buss SJ, Becher T, Bojara W, Weiss C, Papavassiliu T, Akin I, Borggrefe M, Schoenberg SO, Haubenreisser H, Overhoff D, Lossnitzer D. Correlation of machine learning computed tomography-based fractional flow reserve with instantaneous wave free ratio to detect hemodynamically significant coronary stenosis. Clin Res Cardiol. 2020 Jun; 109(6):735-745.
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Litwin SE, Coles A, Hill CL, Alhanti B, Pagidipati N, Lee KL, Pellikka PA, Mark DB, Udelson JE, Cooper L, Tardif JC, Hoffmann U, Douglas PS. Discordances between predicted and actual risk in obese patients with suspected cardiac ischaemia. Heart. 2020 02; 106(4):273-279.
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Baumann S, Renker M, Schoepf UJ, De Cecco CN, Coenen A, De Geer J, Kruk M, Kim YH, Albrecht MH, Duguay TM, Jacobs BE, Bayer RR, Litwin SE, Weiss C, Akin I, Borggrefe M, Yang DH, Kepka C, Persson A, Nieman K, Tesche C. 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.
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Bhatt DL, Steg PG, Mehta SR, Leiter LA, Simon T, Fox K, Held C, Andersson M, Himmelmann A, Ridderstråle W, Chen J, Song Y, Diaz R, Goto S, James SK, Ray KK, Parkhomenko AN, Kosiborod MN, McGuire DK, Harrington RA. Ticagrelor in patients with diabetes and stable coronary artery disease with a history of previous percutaneous coronary intervention (THEMIS-PCI): a phase 3, placebo-controlled, randomised trial. Lancet. 2019 Sep 28; 394(10204):1169-1180.
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Zhou F, Wang YN, Schoepf UJ, Tesche C, Tang CX, Zhou CS, Xu L, Hou Y, Zheng MW, Yan J, Lu MJ, Lu GM, Zhang DM, Zhang B, Zhang JY, Zhang LJ. Diagnostic Performance of Machine Learning Based CT-FFR in Detecting Ischemia in Myocardial Bridging and Concomitant Proximal Atherosclerotic Disease. Can J Cardiol. 2019 11; 35(11):1523-1533.