Machine-Learning-Based In-Hospital Mortality Prediction for Transcatheter Mitral Valve Repair in the United States

BACKGROUND: Transcatheter mitral valve repair utilization has increased significantly in the United States over the last years. Yet, a risk-prediction tool for adverse events has not been developed. We aimed to generate a machine-learning-based algorithm to predict in-hospital mortality after TMVR....

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書誌詳細
出版年:Cardiovasc Revasc Med
主要な著者: Hernandez-Suarez, Dagmar F., Ranka, Sagar, Kim, Yeunjung, Latib, Azeem, Wiley, Jose, Lopez-Candales, Angel, Pinto, Duane S., Gonzalez, Maday C., Ramakrishna, Harish, Sanina, Cristina, Nieves-Rodriguez, Brenda G., Rodriguez-Maldonado, Jovaniel, Maldonado, Roberto Feliu, Rodriguez-Ruiz, Israel J., da Luz Sant’Ana, Istoni, Wiley, Karlo A., Cox-Alomar, Pedro, Villablanca, Pedro A., Roche-Lima, Abiel
フォーマット: Artigo
言語:Inglês
出版事項: 2020
主題:
Article
オンライン･アクセス:https://ncbi.nlm.nih.gov/pmc/articles/PMC7736498/
https://ncbi.nlm.nih.gov/pubmed/32591310
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1016/j.carrev.2020.06.017
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