- Dokumenttyp:
- Zeitschriftenaufsatz
- Autor(en):
- Güldener, Ulrich ; Kessler, Thorsten ; von Scheidt, Moritz ; Hawe, Johann S. ; Gerhard, Beatrix ; Maier, Dieter ; Lachmann, Mark ; Laugwitz, Karl-Ludwig ; Cassese, Salvatore ; Schömig, Albert W. ; Kastrati, Adnan ; Schunkert, Heribert
- Titel:
- Machine Learning Identifies New Predictors on Restenosis Risk after Coronary Artery Stenting in 10,004 Patients with Surveillance Angiography
- Stichworte:
- Article ; artificial intelligence ; coronary artery disease ; machine learning ; percutaneous coronary intervention ; prediction ; restenosis
- Zeitschriftentitel:
- Journal of Clinical Medicine
- Jahr:
- 2023
- Band / Volume:
- 12
- Heft / Issue:
- 8
- Volltext / DOI:
- doi:10.3390/jcm12082941
- Verlag / Institution:
- MDPI
- E-ISSN:
- 2077-0383
- Publikationsdatum:
- 18.04.2023
- CC-Lizenz:
- by, https://creativecommons.org/licenses/by/4.0
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