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JOSS review
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eribul committed Dec 16, 2020
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1 change: 1 addition & 0 deletions README.Rmd
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# coder <img src="man/figures/logo.png" align="right"/>

[![R build status](https://github.com/ropensci/coder/workflows/R-CMD-check/badge.svg)](https://github.com/ropensci/coder/actions) [![codecov](https://codecov.io/gh/ropensci/coder/branch/master/graph/badge.svg)](https://codecov.io/gh/ropensci/coder) [![Project Status: Active – The project has reached a stable, usable state and is being actively developed.](https://www.repostatus.org/badges/latest/active.svg)](https://www.repostatus.org/#active) [![DOI](https://zenodo.org/badge/65975808.svg)](https://zenodo.org/badge/latestdoi/65975808)
[![status](https://joss.theoj.org/papers/49d52b062aa289d7b990b1a0a678d109/status.svg)](https://joss.theoj.org/papers/49d52b062aa289d7b990b1a0a678d109)

<!-- README.md is generated from README.Rmd. Please edit that file -->

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55 changes: 28 additions & 27 deletions README.md
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state and is being actively
developed.](https://www.repostatus.org/badges/latest/active.svg)](https://www.repostatus.org/#active)
[![DOI](https://zenodo.org/badge/65975808.svg)](https://zenodo.org/badge/latestdoi/65975808)
[![status](https://joss.theoj.org/papers/49d52b062aa289d7b990b1a0a678d109/status.svg)](https://joss.theoj.org/papers/49d52b062aa289d7b990b1a0a678d109)

<!-- README.md is generated from README.Rmd. Please edit that file -->

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## Typical use case

- Determining comorbidities before clinical trials
- Discovering adverse events after surgery
- Determining comorbidities before clinical trials
- Discovering adverse events after surgery

**Patient data:** The initial rationale for the package was to classify
patient data based on medical coding. A typical use case would consider
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#> 8 Shuemaker, Lauren 2020-03-29
#> 9 Boucher, Teresa 2020-09-04
#> 10 Le, Soraiya 2020-08-09
#> # ... with 90 more rows
#> # with 90 more rows
```

Those patients (among others) were also recorded in a national patient
Expand All @@ -156,7 +157,7 @@ ex_icd10
#> 8 Sommerville, Dominic 2020-05-03 A227 FALSE
#> 9 Sommerville, Dominic 2020-09-07 H702 FALSE
#> 10 Sommerville, Dominic 2019-12-31 X6051 TRUE
#> # ... with 2,366 more rows
#> # with 2,366 more rows
```

Using those two data sets, as well as a classification scheme
Expand All @@ -175,26 +176,26 @@ ch <-

ch
#> # A tibble: 100 x 25
#> name surgery `myocardial inf~ `congestive hea~ `peripheral vas~
#> name surgery myocardial.infa… congestive.hear… peripheral.vasc…
#> <chr> <date> <lgl> <lgl> <lgl>
#> 1 Arch~ 2020-05-25 FALSE FALSE FALSE
#> 2 Awtr~ 2020-09-20 FALSE FALSE FALSE
#> 3 Bamm~ 2020-03-25 FALSE FALSE FALSE
#> 4 Bank~ 2020-06-18 FALSE FALSE FALSE
#> 5 Bega~ 2020-06-19 FALSE FALSE FALSE
#> 6 Beni~ 2020-02-24 FALSE FALSE FALSE
#> 7 Bhat~ 2020-10-12 FALSE FALSE FALSE
#> 8 Bouc~ 2020-09-04 FALSE FALSE TRUE
#> 9 Carn~ 2020-09-11 FALSE FALSE FALSE
#> 10 Chap~ 2020-05-18 FALSE FALSE FALSE
#> # ... with 90 more rows, and 20 more variables: `cerebrovascular
#> # disease` <lgl>, dementia <lgl>, `chronic pulmonary disease` <lgl>,
#> # `rheumatic disease` <lgl>, `peptic ulcer disease` <lgl>, `mild liver
#> # disease` <lgl>, `diabetes without complication` <lgl>, `hemiplegia or
#> # paraplegia` <lgl>, `renal disease` <lgl>, `diabetes complication` <lgl>,
#> # malignancy <lgl>, `moderate or severe liver disease` <lgl>, `metastatic
#> # solid tumor` <lgl>, `AIDS/HIV` <lgl>, charlson <dbl>, deyo_ramano <dbl>,
#> # dhoore <dbl>, ghali <dbl>, quan_original <dbl>, quan_updated <dbl>
#> 1 Chen… 2020-09-29 FALSE FALSE FALSE
#> 2 Grav… 2020-06-21 FALSE FALSE FALSE
#> 3 Truj… 2020-06-08 FALSE FALSE FALSE
#> 4 Simp… 2020-09-10 FALSE FALSE FALSE
#> 5 Chin… 2020-08-24 FALSE FALSE FALSE
#> 6 Le, … 2020-03-28 FALSE FALSE FALSE
#> 7 Kang… 2020-06-30 FALSE FALSE FALSE
#> 8 Shue… 2020-03-29 FALSE FALSE FALSE
#> 9 Bouc… 2020-09-04 FALSE FALSE TRUE
#> 10 Le, … 2020-08-09 FALSE FALSE FALSE
#> # with 90 more rows, and 20 more variables: cerebrovascular.disease <lgl>,
#> # dementia <lgl>, chronic.pulmonary.disease <lgl>, rheumatic.disease <lgl>,
#> # peptic.ulcer.disease <lgl>, mild.liver.disease <lgl>,
#> # diabetes.without.complication <lgl>, hemiplegia.or.paraplegia <lgl>,
#> # renal.disease <lgl>, diabetes.complication <lgl>, malignancy <lgl>,
#> # moderate.or.severe.liver.disease <lgl>, metastatic.solid.tumor <lgl>,
#> # AIDS.HIV <lgl>, charlson <dbl>, deyo_ramano <dbl>, dhoore <dbl>,
#> # ghali <dbl>, quan_original <dbl>, quan_updated <dbl>
```

How many patients were diagnosed with malignancy?
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#> # A tibble: 7 x 3
#> classcodes regex indices
#> <chr> <chr> <chr>
#> 1 charlson icd10, icd9cm_deyo, icd9cm_enhan~ "charlson, deyo_ramano, dhoore~
#> 1 charlson icd10, icd9cm_deyo, icd9cm_enhan "charlson, deyo_ramano, dhoore
#> 2 cps icd10 "only_ordinary"
#> 3 elixhauser icd10, icd10_short, icd9cm, icd9~ "sum_all, sum_all_ahrq, walrav~
#> 3 elixhauser icd10, icd10_short, icd9cm, icd9 "sum_all, sum_all_ahrq, walrav
#> 4 hip_ae icd10, kva, icd10_fracture ""
#> 5 hip_ae_hail~ icd10, kva ""
#> 5 hip_ae_hail icd10, kva ""
#> 6 knee_ae icd10, kva ""
#> 7 rxriskv atc_pratt, atc_caughey, atc_garl~ "pratt, sum_all"
#> 7 rxriskv atc_pratt, atc_caughey, atc_garl "pratt, sum_all"
```

# Relation to other packages
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