Angiography‐Based Machine Learning for Predicting Fractional Flow Reserve in Intermediate Coronary Artery Lesions

BACKGROUND: An angiography‐based supervised machine learning (ML) algorithm was developed to classify lesions as having fractional flow reserve ≤0.80 versus >0.80. METHODS AND RESULTS: With a 4:1 ratio, 1501 patients with 1501 intermediate lesions were randomized into training versus test sets. B...

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Dettagli Bibliografici
Pubblicato in:J Am Heart Assoc
Autori principali: Cho, Hyungjoo, Lee, June‐Goo, Kang, Soo‐Jin, Kim, Won‐Jang, Choi, So‐Yeon, Ko, Jiyuon, Min, Hyun‐Seok, Choi, Gun‐Ho, Kang, Do‐Yoon, Lee, Pil Hyung, Ahn, Jung‐Min, Park, Duk‐Woo, Lee, Seung‐Whan, Kim, Young‐Hak, Lee, Cheol Whan, Park, Seong‐Wook, Park, Seung‐Jung
Natura: Artigo
Lingua:Inglês
Pubblicazione: John Wiley and Sons Inc. 2019
Soggetti:
Original Research
Accesso online:https://ncbi.nlm.nih.gov/pmc/articles/PMC6405668/
https://ncbi.nlm.nih.gov/pubmed/30764731
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1161/JAHA.118.011685
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