ArticleJournal of biomedical informatics2004
Fever detection from free-text clinical records for biosurveillance.
Article in Journal of biomedical informatics, 2004. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers, 1 of them a synthesis that pooled it.
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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
25 citing papers in PubMed, 1 synthesis or guideline pooled it, 75 citations in OpenAlex.
- A healthy degree of suspicion: A discussion of the implementation of transmission based precautions in the emergency department.Australasian emergency nursing journal : AENJ · 2016Pooled it
- Advocating the potential of artificial intelligence for syndrome discovery in syndromic surveillance systems: A scoping review.iScience · 2026Review
- Identifying Early Signals From Emerging Public Health Events Using Natural Language Processing.Interdisciplinary perspectives on infectious diseases · 2026Article
- The Use and Structure of Emergency Nurses' Triage Narrative Data: Scoping Review.JMIR nursing · 2023Article
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- Facilitating accurate health provider directories using natural language processing.BMC medical informatics and decision making · 2019Article
- Efficient Active Learning for Electronic Medical Record De-identification.AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science · 2019Article
- Optimizing annotation resources for natural language de-identification via a game theoretic framework.Journal of biomedical informatics · 2016Article
- Building a Natural Language Processing Tool to Identify Patients With High Clinical Suspicion for Kawasaki Disease from Emergency Department Notes.Academic emergency medicine : official journal of the Society for Academic Emergency Medicine · 2016Article
- Epidemic surveillance using an electronic medical record: an empiric approach to performance improvement.PloS one · 2014Article
- Chapter 16: text mining for translational bioinformatics.PLoS computational biology · 2013Article
- An exploratory study of a text classification framework for Internet-based surveillance of emerging epidemics.International journal of medical informatics · 2011Article
- Effectiveness of lexico-syntactic pattern matching for ontology enrichment with clinical documents.Methods of information in medicine · 2011Article
- Combining free text and structured electronic medical record entries to detect acute respiratory infections.PloS one · 2010Article
- Article
- Concept Discovery for Pathology Reports using an N-gram Model.Summit on translational bioinformatics · 2010Article
- Paradigm shift or annoying distraction: emerging implications of web 2.0 for clinical practice.Applied clinical informatics · 2010Article
- Detection of disease outbreaks by the use of oral manifestations.Journal of dental research · 2009Article
- Optimizing A syndromic surveillance text classifier for influenza-like illness: Does document source matter?AMIA ... Annual Symposium proceedings. AMIA Symposium · 2008Article
- Defining and applying a method for improving the sensitivity and specificity of an emergency department early event detection system.AMIA ... Annual Symposium proceedings. AMIA Symposium · 2007Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Automatic detection of cases of febrile illness may have potential for early detection of outbreaks of infectious disease either by identification of anomalous numbers of febrile illness or in concert with other information in diagnosing specific syndromes, such as febrile respiratory syndrome. At most institutions, febrile information is contained only in free-text clinical records. We compared the sensitivity and specificity of three fever detection algorithms for detecting fever from free-text. Keyword CC and CoCo classified patients based on triage chief complaints; Keyword HP classified patients based on dictated emergency department reports. Keyword HP was the most sensitive (sensitivity 0.98, specificity 0.89), and Keyword CC was the most specific (sensitivity 0.61, specificity 1.0). Because chief complaints are available sooner than emergency department reports, we suggest a combined application that classifies patients based on their chief complaint followed by classification based on their emergency department report, once the report becomes available.
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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.