ArticleStudies in health technology and informatics2015
Heart Failure Medications Detection and Prescription Status Classification in Clinical Narrative Documents.
Article in Studies in health technology and informatics, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
10 citing papers in PubMed, 11 citations in OpenAlex.
- Scalable medication extraction and discontinuation identification from electronic health records using large language models.Journal of clinical epidemiology · 2026Article
- Overview of the 2022 n2c2 shared task on contextualized medication event extraction in clinical notes.Journal of biomedical informatics · 2023Review
- Extracting medication changes in clinical narratives using pre-trained language models.Journal of biomedical informatics · 2023Article
- Toward Understanding Clinical Context of Medication Change Events in Clinical Narratives.AMIA ... Annual Symposium proceedings. AMIA Symposium · 2021Article
- Clinical concept extraction: A methodology review.Journal of biomedical informatics · 2020Review
- Using natural language processing methods to classify use status of dietary supplements in clinical notes.BMC medical informatics and decision making · 2018Article
- Clinical Data Reuse or Secondary Use: Current Status and Potential Future Progress.Yearbook of medical informatics · 2017Review
- Congestive heart failure information extraction framework for automated treatment performance measures assessment.Journal of the American Medical Informatics Association : JAMIA · 2017Article
- Big data analytics to improve cardiovascular care: promise and challenges.Nature reviews. Cardiology · 2016Review
- Classification of Contextual Use of Left Ventricular Ejection Fraction Assessments.Studies in health technology and informatics · 2015Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors at 2 institutions in 1 country.
Funding
Abstract
Angiotensin Converting Enzyme Inhibitors (ACEI) and Angiotensin II Receptor Blockers (ARB) are two common medication classes used for heart failure treatment. The ADAHF (Automated Data Acquisition for Heart Failure) project aimed at automatically extracting heart failure treatment performance metrics from clinical narrative documents, and these medications are an important component of the performance metrics. We developed two different systems to detect these medications, rule-based and machine learning-based. The rule-based system used dictionary lookups with fuzzy string searching and showed successful performance even if our corpus contains various misspelled medications. The machine learning-based system uses lexical and morphological features and produced similar results. The best performance was achieved when combining the two methods, reaching 99.3% recall and 98.8% precision. To determine the prescription status of each medication (i.e., active, discontinued, or negative), we implemented a SVM classifier with lexical features and achieved good performance, reaching 95.49% accuracy, in a five-fold cross-validation evaluation.
Indexed as
Identifiers
26262123PMC5009609W1138636859What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.