TY  - JOUR
AU  - Schnorr, Isabel
AU  - Andreas, Stefanie
AU  - Schumann, Linnea
AU  - Hahn, Svenja
AU  - Vehreschild, Jörg Janne
AU  - Maier, Daniel
TI  - ATCodeR: a dictionary-based R-tool to standardize medication free-text.
JO  - Scientific reports
VL  - 15
IS  - 1
SN  - 2045-2322
CY  - [London]
PB  - Springer Nature
M1  - DKFZ-2025-00765
SP  - 12252
PY  - 2025
AB  - Over the past decades, oncology treatment paradigms have developed significantly. Yet, the often unstructured nature of substance-related documentation in medical records presents a time-consuming challenge for analyzing treatment patterns and outcomes. To advance oncological research further, clinical data science must offer solutions that facilitate research and analysis with real-world data (RWD). The present contribution introduces a user-friendly R-tool designed to transform free-text medication entries into the structured Anatomical Therapeutic Chemical (ATC) Classification System by applying a dictionary-based approach. The resulting output is a structured data frame containing columns for antineoplastic medication, other medications, and supplementary information. For accuracy validation, 561 data entries from an evaluation data set were reviewed, consisting of 935 tokens. 88.5
KW  - Humans
KW  - Antineoplastic Agents: therapeutic use
KW  - Antineoplastic Agents: classification
KW  - Neoplasms: drug therapy
KW  - Software
KW  - ATC code (Other)
KW  - Dictionary (Other)
KW  - Language processing (Other)
KW  - Medication dictionary (Other)
KW  - R-tool (Other)
KW  - Standardizing free-text (Other)
KW  - Substance dictionary (Other)
KW  - Antineoplastic Agents (NLM Chemicals)
LB  - PUB:(DE-HGF)16
C6  - pmid:40211013
DO  - DOI:10.1038/s41598-025-97150-9
UR  - https://inrepo02.dkfz.de/record/300319
ER  -