An explainable machine learning-based phenomapping strategy for adaptive predictive enrichment in randomized clinical trials

Randomized clinical trials (RCT) represent the cornerstone of evidence-based medicine but are resource-intensive. We propose and evaluate a machine learning (ML) strategy of adaptive predictive enrichment through computational trial phenomaps to optimize RCT enrollment. In simulated group sequential...

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Detalles Bibliográficos
Autores principales: Oikonomou, Evangelos K., Thangaraj, Phyllis M., Bhatt, Deepak L., Ross, Joseph S., Young, Lawrence H., Krumholz, Harlan M., Suchard, Marc A., Khera, Rohan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2023
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10673945/
https://www.ncbi.nlm.nih.gov/pubmed/38001154
http://dx.doi.org/10.1038/s41746-023-00963-z

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10673945/
https://www.ncbi.nlm.nih.gov/pubmed/38001154
http://dx.doi.org/10.1038/s41746-023-00963-z

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