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Displaying results 1 - 8 of 11
  • Content Type: Abstract

    Case detection from chief complaints suffers from low to moderate sensitivity. Emergency Department (ED) reports contain detailed clinical information that could improve case detection ability and enhance outbreak… read more
    … from ED reports, such as: How many new patients have come to the ED with acute lower respiratory symptoms? Of the … called Topaz can identify acute episodes of 55 clinical con- ditions described in emergency department notes. … from ED reports, such as: • How many new patients have come to the ED with acute lower respiratory symptoms? • Of …
  • Content Type: Abstract

    We are developing a Bayesian surveillance system for realtime surveillance and characterization of outbreaks that incorporates a variety of data elements, including free-text clinical reports. An existing natural language processing (… read more
    … language processing system for real-time surveillance WW Chapman, M Conway, JN Dowling, F-C Tsui, Q Li, LM … Journal 2011, 4:s68. doi: 10.3134/ehtj.10.068 & 2011 WW Chapman et al.; licensee Emerging Health Threats Journal. www.eht-journal.org 7 challenges are caused less by NLP …
  • Content Type: Abstract

    Ontologies representing knowledge from the public health and surveillance domains currently exist. However, they focus on infectious diseases (infectious disease ontology), reportable diseases (PHSkbFretired) and internet surveillance… read more
    … Pittsburgh, PA, USA E-mail: michaelambroseconway@gmail.com Objective To develop an application ontologyFthe … Conway et al.; licensee Emerging Health Threats Journal. www.eht-journal.org 15 radiology finding). Further, these … Health Threats Journal M Conway et al. 2011, 4:s73 www.eht-journal.org page 2/2 16 …
  • Content Type: Abstract

    Current methods for influenza surveillance include laboratory confirmed case reporting, sentinel physician reporting of Influenza-Like-Illness (ILI) and chief-complaint monitoring from emergency departments (EDs). The current… read more
    … Tsui et al.; licensee Emerging Health Threats Journal. www.eht-journal.org 95 Conclusions We demonstrate utility … area [online] 2009 cited. Available from: http://kdka.com/health/H1N1.flu.deaths. 2.1321133.html. Automated … Health Threats Journal F-C Tsui et al. 2011, 4:s117 www.eht-journal.org page 2/2 96 …
  • Content Type: Abstract

    There exists no standard set of syndromes for syndromic surveillance, and available syndromic case definitions demonstrate substantial heterogeneity of findings constituting the definition. Many syndromic case definitions require… read more
    … Author JND manu- ally classified the patients’ chief com- plaints into febrile syndromic catego- ries using the … for manual classification of chief complaints when com- pared to criterion standard classification for five … Proc AMIA Annu Fall Symp 2002:1030. 2. Chapman WW, Dowling JN, Wagner MW. Gener- ating a reliable reference …
  • Content Type: Abstract

    The Extended Syndromic Surveillance Ontology (ESSO) is an open source terminological ontology designed to facilitate the text mining of clinical reports in English [1,2]. At the core of ESSO are 279 clinical concepts (for example, fever, confusion,… read more
    … Syndromic Surveillance Ontology: http://code.google. com/p/ss-ontology/. 3. Chapman W, Dowling J, Baer A, … *Mike Conway E-mail: michaelambroseconway@gmail.com (page number not for citation purpose) Table 1. Concepts … 11198 - DOI: 10.3402/ehtj.v4i0.11198 http://code.google.com/p/ss-ontology/ http://code.google.com/p/ss-ontology/ …
  • Content Type: Abstract

    Automated syndromic surveillance systems often classify patients into syndromic categories based on free-text chief complaints. Chief complaints (CC) demonstrate low to moderate sensitivity in identifying syndromic cases. Emergency Department (ED)… read more
    … a Random Forests Classifier. Gold Standard Classification com- prised majority vote of three physicians reading ED …
  • Content Type: Abstract

    This paper describes a Bayesian algorithm for diagnosing the CDC Category A diseases, namely, anthrax, smallpox, tularemia, botulism and hemorrhagic fever, using emergency department chief complaints. The algorithm was evaluated on real data and on… read more
    … of Biosur- veillance (Elsevier, 2006). [2] http://www.bt.cdc.gov/agent/agentlist-category.asp [3] Cooper GF, … Further Information: Gregory Cooper, gfc@cbmi.pitt.edu, www.cbmi.pitt.edu/panda Advances in Disease Surveillance …