ArticleJournal of biomedical informatics2015
Agile text mining for the 2014 i2b2/UTHealth Cardiac risk factors challenge.
Article in Journal of biomedical informatics, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers, 1 of them a synthesis that pooled it.
What it found
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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
19 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Using Natural Language Processing to Measure and Improve Quality of Diabetes Care: A Systematic Review.Journal of diabetes science and technology · 2021Pooled it
- MedADL: high-throughput information extraction of functional status from electronic health records to advance frailty assessment in older adults.The journals of gerontology. Series A, Biological sciences and medical sciences · 2026Article
- IgAN and Risks of Kidney and Cardiovascular Events and Death.Kidney international reports · 2026Article
- Text mining for case report articles on "peritoneal dialysis" from PubMed database.Therapeutic apheresis and dialysis : official peer-reviewed journal of the International Society for Apheresis, the Japanese Society for Apheresis, the Japanese Society for Dialysis Therapy · 2025Article
- Developing Clinical Risk Prediction Models for Worsening Heart Failure Events and Death by Left Ventricular Ejection Fraction.Journal of the American Heart Association · 2023Article
- Named Entity Recognition in Electronic Health Records: A Methodological Review.Healthcare informatics research · 2023Article
- Large-scale identification of undiagnosed hepatic steatosis using natural language processing.EClinicalMedicine · 2023Article
- Heart disease risk factors detection from electronic health records using advanced NLP and deep learning techniques.Scientific reports · 2023Article
- Nd:YAG capsulotomy incidence associated with five different single-piece monofocal intraocular lenses: a 3-year Spanish real-world evidence study of 8293 eyes.Eye (London, England) · 2022Article
- Identifying Cases of Shoulder Injury Related to Vaccine Administration (SIRVA) in the United States: Development and Validation of a Natural Language Processing Method.JMIR public health and surveillance · 2022Article
- A Natural Language Processing-Based Approach for Identifying Hospitalizations for Worsening Heart Failure Within an Integrated Health Care Delivery System.JAMA network open · 2021Article
- Clinical concept extraction: A methodology review.Journal of biomedical informatics · 2020Review
- Open Agile text mining for bioinformatics: the PubAnnotation ecosystem.Bioinformatics (Oxford, England) · 2019Article
- Automatic prediction of coronary artery disease from clinical narratives.Journal of biomedical informatics · 2017Article
- Automatic health record review to help prioritize gravely ill Social Security disability applicants.Journal of the American Medical Informatics Association : JAMIA · 2017Article
- Article
- Identifying risk factors for heart disease over time: Overview of 2014 i2b2/UTHealth shared task Track 2.Journal of biomedical informatics · 2015Review
- Practical applications for natural language processing in clinical research: The 2014 i2b2/UTHealth shared tasks.Journal of biomedical informatics · 2015Article
- Clinical concept annotation with contextual word embedding in active transfer learning environment.Digital healthArticle
Corrections and comments
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Authors and funding
5 authors.
Funding
Abstract
This paper describes the use of an agile text mining platform (Linguamatics' Interactive Information Extraction Platform, I2E) to extract document-level cardiac risk factors in patient records as defined in the i2b2/UTHealth 2014 challenge. The approach uses a data-driven rule-based methodology with the addition of a simple supervised classifier. We demonstrate that agile text mining allows for rapid optimization of extraction strategies, while post-processing can leverage annotation guidelines, corpus statistics and logic inferred from the gold standard data. We also show how data imbalance in a training set affects performance. Evaluation of this approach on the test data gave an F-Score of 91.7%, one percent behind the top performing system.
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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.