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

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-fold stratif...

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Detalles Bibliográficos
Autores principales: Singh, Vikash, Pencina, Michael, Einstein, Andrew J., Liang, Joanna X., Berman, Daniel S., Slomka, Piotr
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2021
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8280147/
https://www.ncbi.nlm.nih.gov/pubmed/34262098
http://dx.doi.org/10.1038/s41598-021-93651-5

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8280147/
https://www.ncbi.nlm.nih.gov/pubmed/34262098
http://dx.doi.org/10.1038/s41598-021-93651-5

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