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 part...
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Published in | Bioinformatics advances Vol. 2; no. 1; p. vbac041 |
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Main Authors | , , |
Format | Journal Article |
Language | English |
Published |
England
Oxford University Press
2022
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Abstract | 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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AbstractList | 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. 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. 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 data are available at online. 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.SummaryThe 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.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.Availability and implementationdipm 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 data are available at Bioinformatics Advances online.Supplementary informationSupplementary data are available at Bioinformatics Advances online. 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. |
Author | Li, Cai Chen, Victoria Zhang, Heping |
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Cites_doi | 10.1073/pnas.0709868104 10.1186/s13073-016-0388-7 10.1007/978-3-030-46161-4_16 10.1111/biom.12593 10.1093/biostatistics/kxaa021 10.1200/JCO.2000.18.1.94 10.1038/nrg.2016.86 |
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The Depth Importance in Precision Medicine (DIPM) method is a classification tree designed for the identification of subgroups relevant to the... The Depth Importance in Precision Medicine (DIPM) method is a classification tree designed for the identification of subgroups relevant to the precision... Summary The Depth Importance in Precision Medicine (DIPM) method is a classification tree designed for the identification of subgroups relevant to the... |
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Title | dipm: an R package implementing the Depth Importance in Precision Medicine (DIPM) tree and Forest-based method |
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