Machine learning paving the way for successful antegrade crossing of total chronic coronary occlusions
- PMID: 39790205
- PMCID: PMC11707474
- DOI: 10.21037/cdt-24-423
Machine learning paving the way for successful antegrade crossing of total chronic coronary occlusions
Keywords: Coronary artery disease (CAD); antegrade crossing; artificial intelligence (AI); chronic total occlusion (CTO); machine learning (ML).
Conflict of interest statement
Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://cdt.amegroups.com/article/view/10.21037/cdt-24-423/coif). P.B. reports consulting activities and honoraria for lectures: AstraZeneca, Bayer Vital, Thieme, Diaplan, BNK (Bundesverband Niedergelassener Kardiologen), Bristol-Myers Squibb, Daiichi Sankyo, Novo Nordisk, Pfizer and Sanofi Aventis; grants from German Heart Foundation; and travel fees from Bayer Vital and Daiichi Sankyo. D.W. reports institutional grants (trial support) from Abiomed, and honoraria for lectures from AstraZeneca, Bayer Vital, Edwards, Medtronic, Meril and Novartis. The other author has no conflicts of interest to declare.
Comment on
-
Predicting Successful Chronic Total Occlusion Crossing With Primary Antegrade Wiring Using Machine Learning.JACC Cardiovasc Interv. 2024 Jul 22;17(14):1707-1716. doi: 10.1016/j.jcin.2024.04.043. Epub 2024 Jul 3. JACC Cardiovasc Interv. 2024. PMID: 38970585
References
-
- Radke P. Künstliche Intelligenz in der kardiovaskulären Medizin-Status und Perspektiven. Aktuelle Kardiologie 2023;12:433-8. 10.1055/a-2146-0667 - DOI
Publication types
LinkOut - more resources
Full Text Sources
Miscellaneous