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(v3.0.1.9005) re-add tidymodels implementation

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dr. M.S. (Matthijs) Berends
2025-12-21 12:19:43 +01:00
parent 225c73f7e7
commit 151af21f38
16 changed files with 502 additions and 61 deletions
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R/data.R
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@@ -282,7 +282,7 @@
#' Data Set with Clinical Breakpoints for SIR Interpretation
#'
#' @description Data set containing clinical breakpoints to interpret MIC and disk diffusion to SIR values, according to international guidelines. This dataset contain breakpoints for humans, `r length(unique(clinical_breakpoints$host[!clinical_breakpoints$host %in% clinical_breakpoints$type]))` different animal groups, and ECOFFs.
#' @description Data set containing clinical breakpoints to interpret MIC and disk diffusion to SIR values, according to international guidelines. This data set contains breakpoints for humans, `r length(unique(clinical_breakpoints$host[!clinical_breakpoints$host %in% clinical_breakpoints$type]))` different animal groups, and ECOFFs.
#'
#' These breakpoints are currently implemented:
#' - For **clinical microbiology**: EUCAST `r min(as.integer(gsub("[^0-9]", "", subset(AMR::clinical_breakpoints, guideline %like% "EUCAST" & type == "human")$guideline)))`-`r max(as.integer(gsub("[^0-9]", "", subset(AMR::clinical_breakpoints, guideline %like% "EUCAST" & type == "human")$guideline)))` and CLSI `r min(as.integer(gsub("[^0-9]", "", subset(AMR::clinical_breakpoints, guideline %like% "CLSI" & type == "human")$guideline)))`-`r max(as.integer(gsub("[^0-9]", "", subset(AMR::clinical_breakpoints, guideline %like% "CLSI" & type == "human")$guideline)))`;
@@ -362,14 +362,14 @@
#' dosage
"dosage"
# TODO #' Data Set with `r format(nrow(esbl_isolates), big.mark = " ")` ESBL Isolates
# TODO #'
# TODO #' A data set containing `r format(nrow(esbl_isolates), big.mark = " ")` microbial isolates with MIC values of common antibiotics and a binary `esbl` column for extended-spectrum beta-lactamase (ESBL) production. This data set contains randomised fictitious data but reflects reality and can be used to practise AMR-related machine learning, e.g., classification modelling with [tidymodels](https://amr-for-r.org/articles/AMR_with_tidymodels.html).
# TODO #' @format A [tibble][tibble::tibble] with `r format(nrow(esbl_isolates), big.mark = " ")` observations and `r ncol(esbl_isolates)` variables:
# TODO #' - `esbl`\cr Logical indicator if the isolate is ESBL-producing
# TODO #' - `genus`\cr Genus of the microorganism
# TODO #' - `AMC:COL`\cr MIC values for 17 antimicrobial agents, transformed to class [`mic`] (see [as.mic()])
# TODO #' @details See our [tidymodels integration][amr-tidymodels] for an example using this data set.
# TODO #' @examples
# TODO #' esbl_isolates
# TODO "esbl_isolates"
#' Data Set with `r format(nrow(esbl_isolates), big.mark = " ")` ESBL Isolates
#'
#' A data set containing `r format(nrow(esbl_isolates), big.mark = " ")` microbial isolates with MIC values of common antibiotics and a binary `esbl` column for extended-spectrum beta-lactamase (ESBL) production. This data set contains randomised fictitious data but reflects reality and can be used to practise AMR-related machine learning, e.g., classification modelling with [tidymodels](https://amr-for-r.org/articles/AMR_with_tidymodels.html).
#' @format A [tibble][tibble::tibble] with `r format(nrow(esbl_isolates), big.mark = " ")` observations and `r ncol(esbl_isolates)` variables:
#' - `esbl`\cr Logical indicator if the isolate is ESBL-producing
#' - `genus`\cr Genus of the microorganism
#' - `AMC:COL`\cr MIC values for 17 antimicrobial agents, transformed to class [`mic`] (see [as.mic()])
#' @details See our [tidymodels integration][amr-tidymodels] for an example using this data set.
#' @examples
#' esbl_isolates
"esbl_isolates"