<li>Getting SNOMED codes of a microorganism, or getting properties of a microorganism based on a SNOMED code (<ahref="./reference/mo_property.html">manual</a>)</li>
<li>Getting LOINC codes of an antibiotic, or getting properties of an antibiotic based on a LOINC code (<ahref="./reference/ab_property.html">manual</a>)</li>
<li>Machine reading the EUCAST and CLSI guidelines from 2011-2020 to translate MIC values and disk diffusion diameters to R/SI (<ahref="https://github.com/msberends/AMR/blob/master/data-raw/rsi_translation.txt">link</a>)</li>
<li>Machine reading the EUCAST and CLSI guidelines from 2011-2020 to translate MIC values and disk diffusion diameters to R/SI (<ahref="./articles/datasets.html">link</a>)</li>
<li>Principal component analysis for AMR (<ahref="./articles/PCA.html">tutorial</a>)</li>
</ul>
</div>
@ -411,7 +411,7 @@ Since you are one of our users, we would like to know how you use the package an
<li>
<p>It <strong>analyses the data</strong> with convenient functions that use well-known methods.</p>
<ul>
<li>Calculate the microbial susceptibility or resistance (and even co-resistance) with the <code><ahref="reference/proportion.html">susceptibility()</a></code> and <code><ahref="reference/proportion.html">resistance()</a></code> functions, or be even more specific with the <code><ahref="reference/proportion.html">proportion_R()</a></code>, <code><ahref="reference/proportion.html">proportion_IR()</a></code>, <code><ahref="reference/proportion.html">proportion_I()</a></code>, <code><ahref="reference/proportion.html">proportion_SI()</a></code> and <code><ahref="reference/proportion.html">proportion_S()</a></code> functions. Similarly, the <em>number</em> of isolates can be determined with the <code><ahref="reference/count.html">count_resistant()</a></code>, <code><ahref="reference/count.html">count_susceptible()</a></code> and <code><ahref="reference/count.html">count_all()</a></code> functions. All these functions can be used with the <code>dplyr</code> package (e.g.in conjunction with <code><ahref="https://rdrr.io/pkg/dplyr/man/summarise.html">summarise()</a></code>)</li>
<li>Calculate the microbial susceptibility or resistance (and even co-resistance) with the <code><ahref="reference/proportion.html">susceptibility()</a></code> and <code><ahref="reference/proportion.html">resistance()</a></code> functions, or be even more specific with the <code><ahref="reference/proportion.html">proportion_R()</a></code>, <code><ahref="reference/proportion.html">proportion_IR()</a></code>, <code><ahref="reference/proportion.html">proportion_I()</a></code>, <code><ahref="reference/proportion.html">proportion_SI()</a></code> and <code><ahref="reference/proportion.html">proportion_S()</a></code> functions. Similarly, the <em>number</em> of isolates can be determined with the <code><ahref="reference/count.html">count_resistant()</a></code>, <code><ahref="reference/count.html">count_susceptible()</a></code> and <code><ahref="reference/count.html">count_all()</a></code> functions. All these functions can be used with the <code>dplyr</code> package (e.g.in conjunction with <code><ahref="https://dplyr.tidyverse.org/reference/summarise.html">summarise()</a></code>)</li>
<li>Plot AMR results with <code><ahref="reference/ggplot_rsi.html">geom_rsi()</a></code>, a function made for the <code>ggplot2</code> package</li>
<li>Predict antimicrobial resistance for the nextcoming years using logistic regression models with the <code><ahref="reference/resistance_predict.html">resistance_predict()</a></code> function</li>
<p>Functions <code><ahref="../reference/get_episode.html">get_episode()</a></code> and <code><ahref="../reference/get_episode.html">is_new_episode()</a></code> to determine (patient) episodes which are not necessarily based on microorganisms. The <code><ahref="../reference/get_episode.html">get_episode()</a></code> function returns the index number of the episode per group, while the <code><ahref="../reference/get_episode.html">is_new_episode()</a></code> function returns values <code>TRUE</code>/<code>FALSE</code> to indicate whether an item in a vector is the start of a new episode. They also support <code>dplyr</code>s grouping (i.e.using <code><ahref="https://rdrr.io/pkg/dplyr/man/group_by.html">group_by()</a></code>):</p>
<p>Functions <code><ahref="../reference/get_episode.html">get_episode()</a></code> and <code><ahref="../reference/get_episode.html">is_new_episode()</a></code> to determine (patient) episodes which are not necessarily based on microorganisms. The <code><ahref="../reference/get_episode.html">get_episode()</a></code> function returns the index number of the episode per group, while the <code><ahref="../reference/get_episode.html">is_new_episode()</a></code> function returns values <code>TRUE</code>/<code>FALSE</code> to indicate whether an item in a vector is the start of a new episode. They also support <code>dplyr</code>s grouping (i.e.using <code><ahref="https://dplyr.tidyverse.org/reference/group_by.html">group_by()</a></code>):</p>
<li><p>Functions <code><ahref="../reference/mo_property.html">mo_is_gram_negative()</a></code> and <code><ahref="../reference/mo_property.html">mo_is_gram_positive()</a></code> as wrappers around <code><ahref="../reference/mo_property.html">mo_gramstain()</a></code>. They always return <code>TRUE</code> or <code>FALSE</code> (except when the input is <code>NA</code> or the MO code is <code>UNKNOWN</code>), thus always return <code>FALSE</code> for species outside the taxonomic kingdom of Bacteria.</p></li>
<li><p>Function <code><ahref="../reference/mo_property.html">mo_is_intrinsic_resistant()</a></code> to test for intrinsic resistance, based on <ahref="https://www.eucast.org/expert_rules_and_intrinsic_resistance/">EUCAST Intrinsic Resistance and Unusual Phenotypes v3.2</a> from 2020.</p></li>
@ -279,15 +279,15 @@
</ul>
</li>
<li>
<p>Some functions are now context-aware when used inside <code>dplyr</code> verbs, such as <code><ahref="https://rdrr.io/pkg/dplyr/man/filter.html">filter()</a></code>, <code><ahref="https://rdrr.io/pkg/dplyr/man/mutate.html">mutate()</a></code> and <code><ahref="https://rdrr.io/pkg/dplyr/man/summarise.html">summarise()</a></code>. This means that then the data argument does not need to be set anymore. This is the case for the new functions <code><ahref="../reference/mo_property.html">mo_is_gram_negative()</a></code>, <code><ahref="../reference/mo_property.html">mo_is_gram_positive()</a></code>, <code><ahref="../reference/mo_property.html">mo_is_intrinsic_resistant()</a></code> and for the existing functions <code><ahref="../reference/first_isolate.html">first_isolate()</a></code>, <code><ahref="../reference/key_antibiotics.html">key_antibiotics()</a></code>, <code><ahref="../reference/mdro.html">mdro()</a></code>, <code><ahref="../reference/mdro.html">brmo()</a></code>, <code><ahref="../reference/mdro.html">mrgn()</a></code>, <code><ahref="../reference/mdro.html">mdr_tb()</a></code>, <code><ahref="../reference/mdro.html">mdr_cmi2012()</a></code>, <code><ahref="../reference/mdro.html">eucast_exceptional_phenotypes()</a></code>. This was already the case for antibiotic selection functions (such as using <code><ahref="../reference/antibiotic_class_selectors.html">penicillins()</a></code> in <code><ahref="https://rdrr.io/pkg/dplyr/man/select.html">dplyr::select()</a></code>).</p>
<p>Some functions are now context-aware when used inside <code>dplyr</code> verbs, such as <code><ahref="https://dplyr.tidyverse.org/reference/filter.html">filter()</a></code>, <code><ahref="https://dplyr.tidyverse.org/reference/mutate.html">mutate()</a></code> and <code><ahref="https://dplyr.tidyverse.org/reference/summarise.html">summarise()</a></code>. This means that then the data argument does not need to be set anymore. This is the case for the new functions <code><ahref="../reference/mo_property.html">mo_is_gram_negative()</a></code>, <code><ahref="../reference/mo_property.html">mo_is_gram_positive()</a></code>, <code><ahref="../reference/mo_property.html">mo_is_intrinsic_resistant()</a></code> and for the existing functions <code><ahref="../reference/first_isolate.html">first_isolate()</a></code>, <code><ahref="../reference/key_antibiotics.html">key_antibiotics()</a></code>, <code><ahref="../reference/mdro.html">mdro()</a></code>, <code><ahref="../reference/mdro.html">brmo()</a></code>, <code><ahref="../reference/mdro.html">mrgn()</a></code>, <code><ahref="../reference/mdro.html">mdr_tb()</a></code>, <code><ahref="../reference/mdro.html">mdr_cmi2012()</a></code>, <code><ahref="../reference/mdro.html">eucast_exceptional_phenotypes()</a></code>. This was already the case for antibiotic selection functions (such as using <code><ahref="../reference/antibiotic_class_selectors.html">penicillins()</a></code> in <code><ahref="https://dplyr.tidyverse.org/reference/select.html">dplyr::select()</a></code>).</p>
<li><p>For all function arguments in the code, it is now defined what the exact type of user input should be (inspired by the <ahref="https://github.com/moodymudskipper/typed"><code>typed</code></a> package). If the user input for a certain function does not meet the requirements for a specific argument (such as the class or length), an informative error will be thrown. This makes the package more robust and the use of it more reproducible and reliable. In total, more than 420 arguments were defined.</p></li>
<p>Improvements for <code><ahref="../reference/as.rsi.html">as.rsi()</a></code>:</p>
<ul>
<li>
<p>Support for using <code>dplyr</code>’s <code><ahref="https://rdrr.io/pkg/dplyr/man/across.html">across()</a></code> to interpret MIC values or disk zone diameters, which also automatically determines the column with microorganism names or codes.</p>
<p>Support for using <code>dplyr</code>’s <code><ahref="https://dplyr.tidyverse.org/reference/across.html">across()</a></code> to interpret MIC values or disk zone diameters, which also automatically determines the column with microorganism names or codes.</p>
<li><p>Cleaning columns in a data.frame now allows you to specify those columns with tidy selection, e.g.<code><ahref="../reference/as.rsi.html">as.rsi(df, col1:col9)</a></code></p></li>
<li><p>Big speed improvement for interpreting MIC values and disk zone diameters. When interpreting 5,000 MIC values of two antibiotics (10,000 values in total), our benchmarks showed a total run time going from 80.7-85.1 seconds to 1.8-2.0 seconds.</p></li>
@ -433,14 +433,14 @@
<ul>
<li><p>Function <code><ahref="../reference/ab_from_text.html">ab_from_text()</a></code> to retrieve antimicrobial drug names, doses and forms of administration from clinical texts in e.g.health care records, which also corrects for misspelling since it uses <code><ahref="../reference/as.ab.html">as.ab()</a></code> internally</p></li>
<li>
<p><ahref="https://tidyselect.r-lib.org/reference/language.html">Tidyverse selection helpers</a> for antibiotic classes, that help to select the columns of antibiotics that are of a specific antibiotic class, without the need to define the columns or antibiotic abbreviations. They can be used in any function that allows selection helpers, like <code><ahref="https://rdrr.io/pkg/dplyr/man/select.html">dplyr::select()</a></code> and <code><ahref="https://tidyr.tidyverse.org/reference/pivot_longer.html">tidyr::pivot_longer()</a></code>:</p>
<p><ahref="https://tidyselect.r-lib.org/reference/language.html">Tidyverse selection helpers</a> for antibiotic classes, that help to select the columns of antibiotics that are of a specific antibiotic class, without the need to define the columns or antibiotic abbreviations. They can be used in any function that allows selection helpers, like <code><ahref="https://dplyr.tidyverse.org/reference/select.html">dplyr::select()</a></code> and <code><ahref="https://tidyr.tidyverse.org/reference/pivot_longer.html">tidyr::pivot_longer()</a></code>:</p>
<li><p>Added <code><ahref="../reference/mo_property.html">mo_domain()</a></code> as an alias to <code><ahref="../reference/mo_property.html">mo_kingdom()</a></code></p></li>
@ -622,14 +622,14 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
<ul>
<li><p>Fixed important floating point error for some MIC comparisons in EUCAST 2020 guideline</p></li>
<li>
<p>Interpretation from MIC values (and disk zones) to R/SI can now be used with <code><ahref="https://rdrr.io/pkg/dplyr/man/mutate_all.html">mutate_at()</a></code> of the <code>dplyr</code> package:</p>
<p>Interpretation from MIC values (and disk zones) to R/SI can now be used with <code><ahref="https://dplyr.tidyverse.org/reference/mutate_all.html"
