Influence of Coronary Calcium on Diagnostic Performance of Machine Learning CT-FFR | Zendy

Christian Tesche | Zendy; Katharina Otani | Zendy; Carlo N. De Cecco | Zendy; Adriaan Coenen | Zendy; Jakob De Geer | Zendy; Mariusz Kruk | Zendy; YoungHak Kim | Zendy; Moritz H. Albrecht | Zendy; Stefan Baumann | Zendy; Matthias Renker | Zendy; Richard R. Bayer | Zendy; Taylor M. Duguay | Zendy; Sheldon E. Litwin | Zendy; Akos VargaSzemes | Zendy; Daniel Steinberg | Zendy; Dong Hyun Yang | Zendy; Cezary Kępka | Zendy; Anders Persson | Zendy; Koen Nieman | Zendy; U. Joseph Schoepf | Zendy

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Influence of Coronary Calcium on Diagnostic Performance of Machine Learning CT-FFR

Author(s) -

Christian Tesche,

Katharina Otani,

Carlo N. De Cecco,

Adriaan Coenen,

Jakob De Geer,

Mariusz Kruk,

YoungHak Kim,

Moritz H. Albrecht,

Stefan Baumann,

Matthias Renker,

Richard R. Bayer,

Taylor M. Duguay,

Sheldon E. Litwin,

Akos VargaSzemes,

Daniel Steinberg,

Dong Hyun Yang,

Cezary Kępka,

Anders Persson,

Koen Nieman,

U. Joseph Schoepf

Publication year - 2020

Publication title -

jacc. cardiovascular imaging

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 5.79

H-Index - 120

eISSN - 1936-878X

pISSN - 1876-7591

DOI - 10.1016/j.jcmg.2019.06.027

Subject(s) - coronary artery calcium , cardiology , medicine , coronary artery disease

This study was conducted to investigate the influence of coronary artery calcium (CAC) score on the diagnostic performance of machine-learning-based coronary computed tomography (CT) angiography (cCTA)-derived fractional flow reserve (CT-FFR).

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