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<p>This algorithm is used by <code><ahref="as.mo.html">as.mo()</a></code> and all the <code><ahref="mo_property.html">mo_*</a></code> functions to determine the most probable match of taxonomic records based on user input.</p>
<p>This algorithm was described in: Berends MS <em>et al.</em> (2022). <strong>AMR: An R Package for Working with Antimicrobial Resistance Data</strong>. <em>Journal of Statistical Software</em>, 104(3), 1-31; <ahref="https://doi.org/10.18637/jss.v104.i03"class="external-link">doi:10.18637/jss.v104.i03</a>
<h2id="matching-score-for-microorganisms">Matching Score for Microorganisms<aclass="anchor"aria-label="anchor"href="#matching-score-for-microorganisms"></a></h2>
<p>With ambiguous user input in <code><ahref="as.mo.html">as.mo()</a></code> and all the <code><ahref="mo_property.html">mo_*</a></code> functions, the returned results are chosen based on their matching score using <code>mo_matching_score()</code>. This matching score \(m\), is calculated as:</p>
<li><p><i>lev</i> is the <ahref="https://en.wikipedia.org/wiki/Levenshtein_distance"class="external-link">Levenshtein distance function</a> (counting any insertion as 1, and any deletion or substitution as 2) that is needed to change <i>x</i> into <i>n</i>;</p></li>
</ul><p>The grouping into human pathogenic prevalence (\(p\)) is based on experience from several microbiological laboratories in the Netherlands in conjunction with international reports on pathogen prevalence:</p>
<p><strong>Group 1</strong> (most prevalent microorganisms) consists of all microorganisms where the taxonomic class is Gammaproteobacteria or where the taxonomic genus is <em>Enterococcus</em>, <em>Staphylococcus</em> or <em>Streptococcus</em>. This group consequently contains all common Gram-negative bacteria, such as <em>Pseudomonas</em> and <em>Legionella</em> and all species within the order Enterobacterales.</p>
<p>All matches are sorted descending on their matching score and for all user input values, the top match will be returned. This will lead to the effect that e.g., <code>"E. coli"</code> will return the microbial ID of <em>Escherichia coli</em> (\(m = 0.688\), a highly prevalent microorganism found in humans) and not <em>Entamoeba coli</em> (\(m = 0.119\), a less prevalent microorganism in humans), although the latter would alphabetically come first.</p>
<h2id="reference-data-publicly-available">Reference Data Publicly Available<aclass="anchor"aria-label="anchor"href="#reference-data-publicly-available"></a></h2>
<p>All data sets in this <code>AMR</code> package (about microorganisms, antibiotics, R/SI interpretation, EUCAST rules, etc.) are publicly and freely available for download in the following formats: R, MS Excel, Apache Feather, Apache Parquet, SPSS, SAS, and Stata. We also provide tab-separated plain text files that are machine-readable and suitable for input in any software program, such as laboratory information systems. Please visit <ahref="https://msberends.github.io/AMR/articles/datasets.html">our website for the download links</a>. The actual files are of course available on <ahref="https://github.com/msberends/AMR/tree/main/data-raw"class="external-link">our GitHub repository</a>.</p>
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<p></p><p><code>AMR</code> (for R). Developed at the <atarget="_blank"href="https://www.rug.nl"class="external-link">University of Groningen</a> in collaboration with non-profit organisations<br><atarget="_blank"href="https://www.certe.nl"class="external-link">Certe Medical Diagnostics and Advice Foundation</a> and <atarget="_blank"href="https://www.umcg.nl"class="external-link">University Medical Center Groningen</a>.</p>
