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Can machine learning unravel unsuspected, clinically important factors predictive of long-term mortality in complex coronary artery disease? A call for ‘big data’
AIMS: Risk stratification and individual risk prediction play a key role in making treatment decisions in patients with complex coronary artery disease (CAD). The aim of this study was to assess whether machine learning (ML) algorithms can improve discriminative ability and identify unsuspected, but...
Autores principales: | Ninomiya, Kai, Kageyama, Shigetaka, Garg, Scot, Masuda, Shinichiro, Kotoku, Nozomi, Revaiah, Pruthvi C, O’leary, Neil, Onuma, Yoshinobu, Serruys, Patrick W |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10232230/ https://www.ncbi.nlm.nih.gov/pubmed/37265868 http://dx.doi.org/10.1093/ehjdh/ztad014 |
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