readAtcMapIntoHashMapAtcCodesAtcNames

Processes the input file db-atc.map to form a HashMap containing the drug names with ATC codes

Analysis and visualization of similarities between epilepsy ontologies based on text mining results by comparing ranked lists of co-occurring drug terms in the BioASQ corpus. The ranked result lists of neurological drug terms co-occurring with terms from the epilepsy ontologies EpSO, ESSO, EPILONT, EPISEM and FENICS undergo further analysis. The source data to create the ranked lists of drug names is produced using the text mining workflows described in Mueller, Bernd and Hagelstein, Alexandra (2016) <doi:10.4126/FRL01-006408558>, Mueller, Bernd et al. (2017) <doi:10.1007/978-3-319-58694-6_22>, Mueller, Bernd and Rebholz-Schuhmann, Dietrich (2020) <doi:10.1007/978-3-030-43887-6_52>, and Mueller, Bernd et al. (2022) <doi:10.1186/s13326-021-00258-w>.

Bernd Mueller

epos

Epilepsy Ontologies' Similarities

readAtcMapIntoHashMapAtcCodesAtcNames function

<dl><dt>filename</dt>
<dd>character vector with the file name of the file db-atc.map</dd>
<dt>seperator</dt>
<dd>character vector with the seperator used within the map-file</dd></dl>

Arguments

Processes the input file db-atc.map to form a HashMap containing the drug names with ATC codes — readAtcMapIntoHashMapAtcCodesAtcNames

<dl>

<dt>filename</dt>
<dd>character vector with the file name of the file db-atc.map</dd>


<dt>seperator</dt>
<dd>character vector with the seperator used within the map-file</dd>

</dl>

State of Data and AI Literacy Report 2025

readAtcMapIntoHashMapAtcCodesAtcNames: Processes the input file db-atc.map to form a HashMap containing the drug names with ATC codes

Description

Usage

Value

Arguments

Examples