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(v1.3.0.9000) support across() in as.rsi()
2020-08-10 11:44:58 +02:00
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.3.0.9000</span>
(v1.3.0) remove vignettes from CRAN
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Conduct AMR analysis
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Predict antimicrobial resistance
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<h1 data-toc-skip>Welcome to the AMR package</h1>
<h4 class="author">Matthijs S. Berends</h4>
(v1.3.0.9000) support across() in as.rsi()
2020-08-10 11:44:58 +02:00
<h4 class="date">10 August 2020</h4>
(v1.3.0) remove vignettes from CRAN
2020-07-31 11:39:56 +02:00
<small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/master/vignettes/welcome_to_AMR.Rmd"><code>vignettes/welcome_to_AMR.Rmd</code></a></small>
<div class="hidden name"><code>welcome_to_AMR.Rmd</code></div>
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<div id="welcome-to-the-amr-package" class="section level1">
<h1 class="hasAnchor">
<a href="#welcome-to-the-amr-package" class="anchor"></a>Welcome to the AMR package</h1>
<p><code>AMR</code> is a free, open-source and independent R package 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 antimicrobial resistance data analysis, that can therefore empower epidemiological analyses to continuously enable surveillance and treatment evaluation in any setting.</p>
<p>After installing this package, R knows <strong>~70,000 distinct microbial species</strong> and all <strong>~550 antibiotic, antimycotic and antiviral drugs</strong> by name and code (including ATC, EARS-NET, LOINC and SNOMED CT), and knows all about valid R/SI and MIC values. It supports any data format, including WHONET/EARS-Net data.</p>
<p>This package is fully independent of any other R package and works on Windows, macOS and Linux with all versions of R since R-3.0.0 (April 2013). <strong>It was designed to work in any setting, including those with very limited resources</strong>. It was created for both routine data analysis and academic research at the Faculty of Medical Sciences of the University of Groningen, in collaboration with non-profit organisations Certe Medical Diagnostics and Advice and University Medical Center Groningen. This R package is actively maintained (see Changelog) and is free software (see Copyright).</p>
<p>Since its first public release in early 2018, this package has been downloaded from more than 100 countries.</p>
<div id="usage-examples" class="section level2">
<h2 class="hasAnchor">
<a href="#usage-examples" class="anchor"></a>Usage examples</h2>
<p>This package can be used for:</p>
<ul>
<li>Reference for the taxonomy of microorganisms, since the package contains all microbial (sub)species from the Catalogue of Life and List of Prokaryotic names with Standing in Nomenclature</li>
<li>Interpreting raw MIC and disk diffusion values, based on the latest CLSI or EUCAST guidelines</li>
<li>Retrieving antimicrobial drug names, doses and forms of administration from clinical health care records</li>
<li>Determining first isolates to be used for AMR analysis</li>
<li>Calculating antimicrobial resistance</li>
<li>Determining multi-drug resistance (MDR) / multi-drug resistant organisms (MDRO)</li>
<li>Calculating (empirical) susceptibility of both mono therapy and combination therapies</li>
<li>Predicting future antimicrobial resistance using regression models</li>
<li>Getting properties for any microorganism (like Gram stain, species, genus or family)</li>
<li>Getting properties for any antibiotic (like name, code of EARS-Net/ATC/LOINC/PubChem, defined daily dose or trade name)</li>
<li>Plotting antimicrobial resistance</li>
<li>Applying EUCAST expert rules</li>
<li>Getting SNOMED codes of a microorganism, or getting properties of a microorganism based on a SNOMED code</li>
<li>Getting LOINC codes of an antibiotic, or getting properties of an antibiotic based on a LOINC code</li>
<li>Machine reading the EUCAST and CLSI guidelines from 2011-2020 to translate MIC values and disk diffusion diameters to R/SI</li>
<li>Principal component analysis for AMR</li>
</ul>
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<nav id="toc" data-toggle="toc"><h2 data-toc-skip>Contents</h2>
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<p>Developed by <a href="https://www.rug.nl/staff/m.s.berends/">Matthijs S. Berends</a>, <a href="https://www.rug.nl/staff/c.f.luz/">Christian F. Luz</a>, <a href="https://www.rug.nl/staff/a.w.friedrich/">Alexander W. Friedrich</a>, <a href="https://www.rug.nl/staff/b.sinha/">Bhanu N. M. Sinha</a>, <a href="https://www.rug.nl/staff/c.j.albers/">Casper J. Albers</a>, <a href="https://www.rug.nl/staff/c.glasner/">Corinna Glasner</a>.</p>
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