P281424/AMR
1
0
Fork 0
mirror of https://github.com/msberends/AMR.git synced 2025-07-08 11:51:59 +02:00
Code Releases Activity

Built site for AMR@2.1.1.9252: abee2a9

Browse Source
This commit is contained in:
github-actions
2025-04-25 09:27:03 +00:00
parent 6f158d57f9
commit 9481aa9987
87 changed files with 124 additions and 116 deletions
Download Patch File Download Diff File Expand all files Collapse all files

8
reference/AMR.html
View File

@ -1,13 +1,13 @@
<!DOCTYPE html>
<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><title>The AMR Package — AMR • AMR (for R)</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="../deps/Lato-0.4.10/font.css" rel="stylesheet"><link href="../deps/Fira_Code-0.4.10/font.css" rel="stylesheet"><link href="../deps/font-awesome-6.5.2/css/all.min.css" rel="stylesheet"><link href="../deps/font-awesome-6.5.2/css/v4-shims.min.css" rel="stylesheet"><script src="../deps/headroom-0.11.0/headroom.min.js"></script><script src="../deps/headroom-0.11.0/jQuery.headroom.min.js"></script><script src="../deps/bootstrap-toc-1.0.1/bootstrap-toc.min.js"></script><script src="../deps/clipboard.js-2.0.11/clipboard.min.js"></script><script src="../deps/search-1.0.0/autocomplete.jquery.min.js"></script><script src="../deps/search-1.0.0/fuse.min.js"></script><script src="../deps/search-1.0.0/mark.min.js"></script><!-- pkgdown --><script src="../pkgdown.js"></script><link href="../extra.css" rel="stylesheet"><script src="../extra.js"></script><meta property="og:title" content="The AMR Package — AMR"><meta name="description" content="Welcome to the AMR package.
The AMR package is a free and open-source R package with zero dependencies to simplify the analysis and prediction of Antimicrobial Resistance (AMR) and to work with microbial and antimicrobial data and properties, by using evidence-based methods. Our aim is to provide a standard for clean and reproducible AMR data analysis, that can therefore empower epidemiological analyses to continuously enable surveillance and treatment evaluation in any setting. Many different researchers from around the globe are continually helping us to make this a successful and durable project!
The AMR package is a peer-reviewed, free and open-source R package with zero dependencies to simplify the analysis and prediction of Antimicrobial Resistance (AMR) and to work with microbial and antimicrobial data and properties, by using evidence-based methods. Our aim is to provide a standard for clean and reproducible AMR data analysis, that can therefore empower epidemiological analyses to continuously enable surveillance and treatment evaluation in any setting. Many different researchers from around the globe are continually helping us to make this a successful and durable project!
This work was published in the Journal of Statistical Software (Volume 104(3); doi:10.18637/jss.v104.i03
) and formed the basis of two PhD theses (doi:10.33612/diss.177417131
and doi:10.33612/diss.192486375
).
After installing this package, R knows ~79 000 microorganisms (updated June 2024) and all ~620 antibiotic, antimycotic and antiviral drugs by name and code (including ATC, EARS-Net, ASIARS-Net, PubChem, LOINC and SNOMED CT), and knows all about valid SIR and MIC values. The integral clinical breakpoint guidelines from CLSI and EUCAST are included, even with epidemiological cut-off (ECOFF) values. It supports and can read any data format, including WHONET data. This package works on Windows, macOS and Linux with all versions of R since R-3.0 (April 2013). It was designed to work in any setting, including those with very limited resources. It was created for both routine data analysis and academic research at the Faculty of Medical Sciences of the public University of Groningen, in collaboration with non-profit organisations Certe Medical Diagnostics and Advice Foundation and University Medical Center Groningen.
The AMR package is available in English, Chinese, Czech, Danish, Dutch, Finnish, French, German, Greek, Italian, Japanese, Norwegian, Polish, Portuguese, Romanian, Russian, Spanish, Swedish, Turkish, and Ukrainian. Antimicrobial drug (group) names and colloquial microorganism names are provided in these languages."><meta property="og:description" content="Welcome to the AMR package.
The AMR package is a free and open-source R package with zero dependencies to simplify the analysis and prediction of Antimicrobial Resistance (AMR) and to work with microbial and antimicrobial data and properties, by using evidence-based methods. Our aim is to provide a standard for clean and reproducible AMR data analysis, that can therefore empower epidemiological analyses to continuously enable surveillance and treatment evaluation in any setting. Many different researchers from around the globe are continually helping us to make this a successful and durable project!
The AMR package is a peer-reviewed, free and open-source R package with zero dependencies to simplify the analysis and prediction of Antimicrobial Resistance (AMR) and to work with microbial and antimicrobial data and properties, by using evidence-based methods. Our aim is to provide a standard for clean and reproducible AMR data analysis, that can therefore empower epidemiological analyses to continuously enable surveillance and treatment evaluation in any setting. Many different researchers from around the globe are continually helping us to make this a successful and durable project!
This work was published in the Journal of Statistical Software (Volume 104(3); doi:10.18637/jss.v104.i03
) and formed the basis of two PhD theses (doi:10.33612/diss.177417131
and doi:10.33612/diss.192486375
@ -21,7 +21,7 @@ The AMR package is available in English, Chinese, Czech, Danish, Dutch, Finnish,
<a class="navbar-brand me-2" href="../index.html">AMR (for R)</a>
<small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">2.1.1.9251</small>
<small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">2.1.1.9252</small>
<button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
@ -65,7 +65,7 @@ The AMR package is available in English, Chinese, Czech, Danish, Dutch, Finnish,
<div class="ref-description section level2">
<p>Welcome to the <code>AMR</code> package.</p>
<p>The <code>AMR</code> package is a <a href="https://amr-for-r.org/#copyright">free and open-source</a> R package with <a href="https://en.wikipedia.org/wiki/Dependency_hell" class="external-link">zero dependencies</a> to simplify the analysis and prediction of Antimicrobial Resistance (AMR) and to work with microbial and antimicrobial data and properties, by using evidence-based methods. <strong>Our aim is to provide a standard</strong> for clean and reproducible AMR data analysis, that can therefore empower epidemiological analyses to continuously enable surveillance and treatment evaluation in any setting. <a href="https://amr-for-r.org/authors.html">Many different researchers</a> from around the globe are continually helping us to make this a successful and durable project!</p>
<p>The <code>AMR</code> package is a peer-reviewed, <a href="https://amr-for-r.org/#copyright">free and open-source</a> R package with <a href="https://en.wikipedia.org/wiki/Dependency_hell" class="external-link">zero dependencies</a> to simplify the analysis and prediction of Antimicrobial Resistance (AMR) and to work with microbial and antimicrobial data and properties, by using evidence-based methods. <strong>Our aim is to provide a standard</strong> for clean and reproducible AMR data analysis, that can therefore empower epidemiological analyses to continuously enable surveillance and treatment evaluation in any setting. <a href="https://amr-for-r.org/authors.html">Many different researchers</a> from around the globe are continually helping us to make this a successful and durable project!</p>
<p>This work was published in the Journal of Statistical Software (Volume 104(3); <a href="https://doi.org/10.18637/jss.v104.i03" class="external-link">doi:10.18637/jss.v104.i03</a>
) and formed the basis of two PhD theses (<a href="https://doi.org/10.33612/diss.177417131" class="external-link">doi:10.33612/diss.177417131</a>
and <a href="https://doi.org/10.33612/diss.192486375" class="external-link">doi:10.33612/diss.192486375</a>