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exam_forecast

Companion analysis to a paper published in the Journal of Digital Imaging.

https://github.com/asbecker/exam_forecast

Science Score: 67.0%

This score indicates how likely this project is to be science-related based on various indicators:

  • ✓
    CITATION.cff file
    Found CITATION.cff file
  • ✓
    codemeta.json file
    Found codemeta.json file
  • ✓
    .zenodo.json file
    Found .zenodo.json file
  • ✓
    DOI references
    Found 4 DOI reference(s) in README
  • ✓
    Academic publication links
    Links to: zenodo.org
  • ○
    Academic email domains
  • ○
    Institutional organization owner
  • ○
    JOSS paper metadata
  • ○
    Scientific vocabulary similarity
    Low similarity (11.8%) to scientific vocabulary

Keywords

forecasting medicine operations radiology resource-management
Last synced: 6 months ago · JSON representation ·

Repository

Companion analysis to a paper published in the Journal of Digital Imaging.

Basic Info
  • Host: GitHub
  • Owner: ASBecker
  • License: mit
  • Language: TeX
  • Default Branch: master
  • Homepage:
  • Size: 60.5 KB
Statistics
  • Stars: 1
  • Watchers: 1
  • Forks: 1
  • Open Issues: 0
  • Releases: 1
Topics
forecasting medicine operations radiology resource-management
Created almost 6 years ago · Last pushed over 4 years ago
Metadata Files
Readme License Citation

README.md

Paper Repository: Automatic Forecasting of Radiology Examination Volume Trends for Optimal Resource Planning and Allocation

<!-- badges: start --> Launch Rstudio Binder DOI <!-- badges: end -->

by Anton S. Becker · Joseph P. Erinjeri · Joshua Chaim · Nicholas Kastango · Pierre Elnajjar · Hedvig Hricak · H. Alberto Vargas

This is the companion analysis to a paper published in the Journal of Digital Imaging.

Preparation

To run the analysis in ExamForecast.Rmd, the following packages need to be installed:

r install.packages( c( "here", "kableExtra", "knitr", "magrittr", "prophet", "readr", "rmarkdown", "stringr", "tidyverse", "timeDate" # Recommended: "rticles" "skimr" ) )

Data Format

The synthetic toy data is provided in the "Data" folder (gzipped csv). It can be read natively by {{readr::read_csv}} or alternatively unzipped by R's native read.csv function. To run a prophet forecast with our own data, replace the csv files with your own data with at least two columns: Date and number of examinations. In order to recycle the code from this repository a column modality_code should be added containing either "CT" or "MRI".

r library(dplyr) here::here("Data", "per_diem_msk.csv.gz") %>% readr::read_csv(show_col_types = FALSE) %>% skimr::skim()

Simple forecast example

For a more comprehensive documentation please refer to the accompanying ExamForecast.Rmd and the official Prophet documentation. Below is a minimal example of a forecast for the next month:

```r library(dplyr) library(prophet)

exams <- here::here("Data", "perdiemmsk.csv.gz") %>% readr::readcsv() %>% filter(modalitycode == "CT") %>% transmute( ds = asdate(examdate), y = n_exams, )

m <- prophet(exams)

pred <- makefuturedataframe(m, 31, "days", include_history = TRUE)

forecast_exams <- predict(m, pred) ```

License

All source code is made available under a MIT or file-specific license. You can freely use and modify the code, without warranty, so long as you provide attribution to the authors/cite the article. See LICENSE.md for the full license text.

Owner

  • Name: Anton Becker
  • Login: ASBecker
  • Kind: user

Citation (CITATION.cff) 

cff-version: 1.2.0
message: "If you use (parts of) this analysis or data, please cite it as below."
authors:
- family-names: "Becker"
  given-names: "Anton S."
  orcid: "https://orcid.org/0000-0001-8372-6496"
- family-names: "Erinjeri"
  given-names: "Joseph"
- family-names: "Kastango"
  given-names: "Nicholas"
title: "Radiology exam volume forecast repository"
version: 1.0
doi: 10.5281/zenodo.5699476
date-released: 2017-12-18
url: "https://github.com/ASBecker/exam_forecast"
preferred-citation:
  type: article
  authors:
  - family-names: "Becker"
    given-names: "Anton S."
    orcid: "https://orcid.org/0000-0001-8372-6496"
  - family-names: "Erinjeri"
    given-names: "Joseph P."
  - family-names: "Chaim"
    given-names: "Joshua"
  - family-names: "Kastango"
    given-names: "Nicholas"
  - family-names: "Elnajjar"
    given-names: "Pierre"
  - family-names: "Hricak"
    given-names: "Hedvig"
  - family-names: "Vargas"
    given-names: "H. Alberto"
  doi: "10.1007/s10278-021-00532-4"
  journal: "Journal of Digital Imaging"
  title: "Automatic Forecasting of Radiology Examination Volume Trends for Optimal Resource Planning and Allocation"
  year: 2021

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Dependencies

DESCRIPTION cran
  • dplyr * depends
  • here * depends
  • kableExtra * depends
  • knitr * depends
  • lubridate * depends
  • magrittr * depends
  • prophet * depends
  • readr * depends
  • rmarkdown * depends
  • rticles * depends
  • skimr * depends
  • stringr * depends
  • tidyverse * depends
  • timeDate * depends
.binder/Dockerfile docker
  • rocker/binder 4.0.5 build