├── analysis
│ ├── bin
│ │ ├── analysis.R # my code for lasso. still work in progress. the first three lines source the functions.R, packages.R and data.R
│ │ ├── data.R # script to clean data
│ │ ├── functions.R # my functions
│ │ ├── packages.R # packages used
│ │ └── tsne-analysis.R # cluster analysis
│ ├── data # this contains the raw data. see bin/data.R for cleaning it.
│ │ ├── DO-NOT-EDIT-ANY-FILES-IN-HERE-BY-HAND
│ │ ├── HNSCCT-input.csv
│ │ └── HNSCCT-outcome.csv
│ ├── paper
│ │ ├── paper_files
│ │ │ └── figure-html
│ │ │ ├── unnamed-chunk-3-1.png
│ │ │ ├── unnamed-chunk-5-1.png
│ │ │ └── unnamed-chunk-7-1.png
│ │ ├── paper.html
│ │ ├── paper.md
│ │ ├── paper.Rmd # source file for paper.
│ │ ├── references.bib
│ │ └── skeleton.bib
│ ├── README.md # description of variables in the data
│ ├── report
│ │ └── descriptive_stats.html # descriptive stats using DataExplorer package
│ └── templates
│ ├── author-info-blocks.lua
│ ├── journal-of-archaeological-science.csl
│ ├── pagebreak.lua
│ ├── scholarly-metadata.lua
│ ├── template.docx
│ └── template.Rmd
├── CONDUCT.md
├── CONTRIBUTING.md
├── DESCRIPTION
├── Dockerfile
├── LICENSE
├── LICENSE.md
├── NAMESPACE
├── radbayes.Rproj
├── README.md
├── README.Rmd
├── references
│ ├── comparing_classifiers
│ │ ├── Benavoli2017_Time_for_a_change_tutorial_for_comparing_multiple_classifiers_through_bayesian_analysis_JMLR.pdf
│ │ └── Corani_ParametricBayesianComparison_slides.pdf
│ ├── multitask
│ │ ├── bayesian multi task.pdf
│ │ └── multi-modal_imaging genetics.pdf
│ ├── radiology
│ │ ├── Beyond imaging: The promise of radiomics.pdf
│ │ ├── Forghani_EurRad_2019_HNSCC cervical node prediction DECT-texture-ML.pdf # Shirin
│ │ ├── Images Are More than pictures_they are data_Radiology 2015.pdf
│ │ ├── machine_learning_methods_for_quantitative_radiomic_biomarkers_sci_reports_2015.pdf # Shirin
│ │ ├── Quantitative_Imaging_of_cancer_in_the_Postgenomic_Era_Radiogenomics_Deep_Learning_and_Habitats.pdf
│ │ ├── Radiomic Features at Contrast-enhanced CT Predict_Radiology_2020.pdf # Shirin
│ │ ├── radiomics_strategies_for_risk_assessment of tumour failure_in_HNNC.pdf # Shirin
│ │ ├── Revealing Tumor Habitats from from texture heterogenietyAnalysis_Sci_Reports.pdf
│ │ ├── Savadjiev2019_Article_Image-basedBiomarkersForSolidT.pdf
│ │ ├── Thierry_Presentation.pdf
│ │ └── Unravelling tumor heterogeneity_habitat_imaging_Sala_2017.pdf
│ ├── RSNA_2019_HNSCC_Dec5 (1).pdf # abstract presented at RSNA conference on this data
│ └── sparsity
│ └── Pironen2017_Sparsity information and regularization_EJS.pdf
└── tests
└── testthat.R
# https://github.com/rocker-org/rocker/wiki/Using-the-RStudio-image
# https://www.digitalocean.com/community/tutorials/how-to-install-and-use-docker-on-ubuntu-16-04
# https://docs.docker.com/engine/reference/run/ which explains the run tags
docker pull sahirbhatnagar/radbayes:latest # pulls the image locally
docker images # see list of images
docker ps -a # also see list of images
docker run -d -p 8787:8787 -e PASSWORD=<YOUR_PASS> --name radbayes sahirbhatnagar/radbayes
# then go to http://localhost:8787
# username is rstudio, password is what you specified
# in R do: setwd('/radbayes/') and then you should see the folder with all the materials in the folder RStudio pane
docker stop radbayes # this can be what you supplied to --name in the above command or the container ID