Predicting Successful Chronic Total Occlusion Crossing With Primary Antegrade Wiring Using Machine Learning-Reference-Cited by-同舟云学术

Predicting Successful Chronic Total Occlusion Crossing With Primary Antegrade Wiring Using Machine Learning

Published:2024-07 Issue:14 Volume:17 Page:1707-1716
ISSN:1936-8798
Container-title:JACC: Cardiovascular Interventions
language:en
Short-container-title:JACC: Cardiovascular Interventions

Author:

Rempakos Athanasios^ORCID,Alexandrou Michaella,Mutlu Deniz^ORCID,Kalyanasundaram Arun,Ybarra Luiz F.^ORCID,Bagur Rodrigo^ORCID,Choi James W.^ORCID,Poommipanit Paul,Khatri Jaikirshan J.,Young Laura,Davies Rhian^ORCID,Benton Stewart,Gorgulu Sevket^ORCID,Jaffer Farouc A.^ORCID,Chandwaney Raj,Jaber Wissam,Rinfret Stephane,Nicholson William,Azzalini Lorenzo^ORCID,Kearney Kathleen E.,Alaswad Khaldoon,Basir Mir B.^ORCID,Krestyaninov Oleg,Khelimskii Dmitrii,Abi-Rafeh Nidal,Elguindy Ahmed,Goktekin Omer,Aygul Nazif^ORCID,Rangan Bavana V.,Mastrodemos Olga C.,Al-Ogaili Ahmed,Sandoval Yader,Burke M. Nicholas,Brilakis Emmanouil S.

Publisher

Elsevier BV

Reference27 articles.

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4. A new algorithm for crossing chronic total occlusions from the Asia Pacific Chronic Total Occlusion Club;Harding;JACC Cardiovasc Interv,2017

5. Global chronic total occlusion crossing algorithm: JACC state-of-the-art review;Wu;J Am Coll Cardiol,2021

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