dipm: an R package implementing the Depth Importance in Precision Medicine (DIPM) tree and Forest-based method

SUMMARY: The Depth Importance in Precision Medicine (DIPM) method is a classification tree designed for the identification of subgroups relevant to the precision medicine setting. In this setting, a relevant subgroup is a subgroup in which subjects perform either especially well or poorly with a par...

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Detalles Bibliográficos
Autores principales: Chen, Victoria, Li, Cai, Zhang, Heping
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2022
Materias:
Application Note
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9245626/
https://www.ncbi.nlm.nih.gov/pubmed/35785020
http://dx.doi.org/10.1093/bioadv/vbac041
Descripción
Sumario:SUMMARY: The Depth Importance in Precision Medicine (DIPM) method is a classification tree designed for the identification of subgroups relevant to the precision medicine setting. In this setting, a relevant subgroup is a subgroup in which subjects perform either especially well or poorly with a particular treatment assignment. Herein, we introduce, dipm, a novel R package that implements the DIPM method using R code that calls a program in C. AVAILABILITY AND IMPLEMENTATION: dipm is available under a GPL-3 licence on CRAN https://cran.r-project.org/web/packages/dipm/index.html and at https://ysph.yale.edu/c2s2/software/dipm. It is continuously being developed at https://github.com/chenvict/dipm. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics Advances online.

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