TCT-527 A data-driven approach combining image-based anatomical features and resting state measurements for the functional assessment of coronary artery disease

TCT-527 A data-driven approach combining image-based anatomical features and resting state measurements for the functional assessment of coronary artery disease

Conclusion The proposed machine learning algorithm, which augments the resting state measurements with patient-specific anatomical features extracted from routine angiograms, demonstrated a high diagnostic accuracy and correlation against invasive FFR, thus potentially obviating the need for hyperem...

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Veröffentlicht in:Journal of the American College of Cardiology 2016-11, Vol.68 (18), p.B212-B213
Hauptverfasser: Calmac, Lucian, Niculescu, Rodica, Badila, Elisabeta, Weiss, Emma, Penes, Daniela, Zamfir, Diana, Itu, Lucian, Lazar, Laszlo, Carp, Marius, Itu, Alexandru, Suciu, Constantin, Passerini, Tiziano, Sharma, Puneet, Georgescu, Bogdan, Comaniciu, Dorin
Format: Artikel
Sprache:eng
Schlagworte:
Accuracy
Algorithms
Cardiology
Cardiovascular
Cardiovascular disease
Coronary vessels
Internal Medicine
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Zusammenfassung:Conclusion The proposed machine learning algorithm, which augments the resting state measurements with patient-specific anatomical features extracted from routine angiograms, demonstrated a high diagnostic accuracy and correlation against invasive FFR, thus potentially obviating the need for hyperemia.
ISSN:0735-1097
1558-3597
DOI:10.1016/j.jacc.2016.09.664