Impact of train/test sample regimen on performance estimate stability of machine learning in cardiovascular imaging

Abstract As machine learning research in the field of cardiovascular imaging continues to grow, obtaining reliable model performance estimates is critical to develop reliable baselines and compare different algorithms. While the machine learning community has generally accepted methods such as k-fol...

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Autores principales: Vikash Singh, Michael Pencina, Andrew J. Einstein, Joanna X. Liang, Daniel S. Berman, Piotr Slomka
Formato: article
Lenguaje:EN
Publicado: Nature Portfolio 2021
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Acceso en línea:https://doaj.org/article/3fbe52b623e04aa399b5b0f5b1e1ff34
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