Negation detection in Dutch clinical texts: an evaluation of rule-based and machine learning methods. (arXiv:2209.00470v1 [cs.CL])

As structured data are often insufficient, labels need to be extracted from
free text in electronic health records when developing models for clinical
information retrieval and decision support systems. One of the most important
contextual properties in clinical text is negation, which indicates the absence
of findings. We aimed to improve large scale extraction of labels by comparing
three methods for negation detection in Dutch clinical notes. We used the
Erasmus Medical Center Dutch Clinical Corpus to compare a rule-based …

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