ArticleJournal of the American Medical Informatics Association : JAMIA
Dictionary construction and identification of possible adverse drug events in Danish clinical narrative text.
Article in Journal of the American Medical Informatics Association : JAMIA. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 33 papers, 1 of them a synthesis that pooled it.
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Who cites it
33 citing papers in PubMed, 1 synthesis or guideline pooled it, 89 citations in OpenAlex.
- Text mining applications in psychiatry: a systematic literature review.International journal of methods in psychiatric research · 2016Pooled it
- Identifying Adverse Drug Events in Clinical Text Using Fine-Tuned Clinical Language Models: Machine Learning Study.JMIR formative research · 2025Article
- Combining unsupervised, supervised and rule-based learning: the case of detecting patient allergies in electronic health records.BMC medical informatics and decision making · 2023Article
- Machine learning-driven clinical decision support system for concept-based searching: a field trial in a Norwegian hospital.BMC medical informatics and decision making · 2023Article
- Language-agnostic pharmacovigilant text mining to elicit side effects from clinical notes and hospital medication records.Basic & clinical pharmacology & toxicology · 2022Article
- Development of a Pipeline for Adverse Drug Reaction Identification in Clinical Notes: Word Embedding Models and String Matching.JMIR medical informatics · 2022Article
- A Multitask Deep Learning Framework for DNER.Computational intelligence and neuroscience · 2022Article
- Prediction of risk of acquiring urinary tract infection during hospital stay based on machine-learning: A retrospective cohort study.PloS one · 2021Article
- Prevalence of Mental Illnesses in Domestic Violence Police Records: Text Mining Study.Journal of medical Internet research · 2020Article
- Implementation and comparison of two text mining methods with a standard pharmacovigilance method for signal detection of medication errors.BMC medical informatics and decision making · 2020Article
- Association between antipsychotic drug dose and length of clinical notes: a proxy of disease severity?BMC medical research methodology · 2020Observational
- Application of Augmented Intelligence for Pharmacovigilance Case Seriousness Determination.Drug safety · 2020Article
- Linking glycemic dysregulation in diabetes to symptoms, comorbidities, and genetics through EHR data mining.eLife · 2019Article
- A rule-based approach to identify patient eligibility criteria for clinical trials from narrative longitudinal records.JAMIA open · 2019Article
- Development of a Controlled Vocabulary-Based Adverse Drug Reaction Signal Dictionary for Multicenter Electronic Health Record-Based Pharmacovigilance.Drug safety · 2019Article
- A classification framework for exploiting sparse multi-variate temporal features with application to adverse drug event detection in medical records.BMC medical informatics and decision making · 2019Article
- Automatic Extraction of Mental Health Disorders From Domestic Violence Police Narratives: Text Mining Study.Journal of medical Internet research · 2018Article
- Clinical Natural Language Processing in languages other than English: opportunities and challenges.Journal of biomedical semantics · 2018Review
- Automatic mining of symptom severity from psychiatric evaluation notes.International journal of methods in psychiatric research · 2018Article
- Review
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Authors and funding
5 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectiveDrugs have tremendous potential to cure and relieve disease, but the risk of unintended effects is always present. Healthcare providers increasingly record data in electronic patient records (EPRs), in which we aim to identify possible adverse events (AEs) and, specifically, possible adverse drug events (ADEs). MATERIALS AND
methodsBased on the undesirable effects section from the summary of product characteristics (SPC) of 7446 drugs, we have built a Danish ADE dictionary. Starting from this dictionary we have developed a pipeline for identifying possible ADEs in unstructured clinical narrative text. We use a named entity recognition (NER) tagger to identify dictionary matches in the text and post-coordination rules to construct ADE compound terms. Finally, we apply post-processing rules and filters to handle, for example, negations and sentences about subjects other than the patient. Moreover, this method allows synonyms to be identified and anatomical location descriptions can be merged to allow appropriate grouping of effects in the same location.
resultsThe method identified 1 970 731 (35 477 unique) possible ADEs in a large corpus of 6011 psychiatric hospital patient records. Validation was performed through manual inspection of possible ADEs, resulting in precision of 89% and recall of 75%. DISCUSSION: The presented dictionary-building method could be used to construct other ADE dictionaries. The complication of compound words in Germanic languages was addressed. Additionally, the synonym and anatomical location collapse improve the method.
conclusionsThe developed dictionary and method can be used to identify possible ADEs in Danish clinical narratives.
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