Impact of machine-learning-based coronary computed tomography angiography–derived fractional flow reserve on decision-making in patients with severe aortic stenosis undergoing transcatheter aortic valve replacement.

Detalles Bibliográficos
Publicado en:European Radiology Vol. 32; no. 9; pp. 6008 - 6017
Autores principales: Brandt, Verena, Schoepf, U. Joseph, Aquino, Gilberto J., Bekeredjian, Raffi, Varga-Szemes, Akos, Emrich, Tilman, Bayer II, Richard R., Schwarz, Florian, Kroencke, Thomas J., Tesche, Christian, Decker, Josua A.
Formato: Journal Article
Publicado: Springer Nature Sep2022
Acceso en línea:Ver este registro en EBSCOhost
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        atl: Impact of machine-learning-based coronary computed tomography angiography–derived fractional flow reserve on decision-making in patients with severe aortic stenosis undergoing transcatheter aortic valve replacement.
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          Brandt, Verena
          Schoepf, U. Joseph
          Aquino, Gilberto J.
          Bekeredjian, Raffi
          Varga-Szemes, Akos
          Emrich, Tilman
          Bayer II, Richard R.
          Schwarz, Florian
          Kroencke, Thomas J.
          Tesche, Christian
          Decker, Josua A.
        affil: Division of Cardiovascular Imaging, Department of Radiology and Radiological Science, Medical University of South Carolina, Ashley River Tower, 5 Courtenay Drive, 29425-2260, Charleston, SC, USA
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      pubtype: Academic Journal
      doctype: Journal Article
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    language: English
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