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

Randomized controlled 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 sequenti...

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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: Cold Spring Harbor Laboratory 2023
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10635225/
https://www.ncbi.nlm.nih.gov/pubmed/37961715
http://dx.doi.org/10.1101/2023.06.18.23291542

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10635225/
https://www.ncbi.nlm.nih.gov/pubmed/37961715
http://dx.doi.org/10.1101/2023.06.18.23291542

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