HealthMap: global infectious disease monitoring through automated classification and visualization of Internet media reports.
Objective: Unstructured electronic information sources, such as news reports, are proving to be valuable inputs for public health surveillance. However, staying abreast of current disease outbreaks requires scouring a continually growing number of disparate news sources and alert services, resulting...
| Publicado en: | Journal of the American Medical Informatics Association Vol. 15; no. 2; pp. 150 - 158 |
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| Autores principales: | , , , , , , , |
| Formato: | pictorial tables/charts Journal Article |
| Publicado: |
Oxford University Press / USA
Mar/Apr2008
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=105728713&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 105728713 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 10675027 FZ9 jtl: Journal of the American Medical Informatics Association issn: 10675027 maglogo: N pubinfo: dt: Mar/Apr2008 vid: 15 iid: 2 pid: 622 pub: Oxford University Press / USA artinfo: ui: 105728713 105728713 NLM18096908 2009871687 10.1197/jamia.m2544 NLM18096908 PMC2274789 105728713 ppf: 150 ppct: 8 formats: tig: atl: HealthMap: global infectious disease monitoring through automated classification and visualization of Internet media reports. aug: au: Freifeld CC Mandl KD Reis BY Brownstein JS Freifeld, Clark C Mandl, Kenneth D Reis, Ben Y Brownstein, John S affil: Children's Hospital Informatics Program, Harvard-MIT Division of Health Sciences and Technology, 300 Longwood Ave., Boston, MA 02115, USA sug: subj: Disease Outbreaks Disease Surveillance Methods Internet Public Health Communicable Diseases Classification Communicable Diseases Diagnosis Communications Media Data Collection Methods Software ab: Objective: Unstructured electronic information sources, such as news reports, are proving to be valuable inputs for public health surveillance. However, staying abreast of current disease outbreaks requires scouring a continually growing number of disparate news sources and alert services, resulting in information overload. Our objective is to address this challenge through the HealthMap.org Web application, an automated system for querying, filtering, integrating and visualizing unstructured reports on disease outbreaks.Design: This report describes the design principles, software architecture and implementation of HealthMap and discusses key challenges and future plans.Measurements: We describe the process by which HealthMap collects and integrates outbreak data from a variety of sources, including news media (e.g., Google News), expert-curated accounts (e.g., ProMED Mail), and validated official alerts. Through the use of text processing algorithms, the system classifies alerts by location and disease and then overlays them on an interactive geographic map. We measure the accuracy of the classification algorithms based on the level of human curation necessary to correct misclassifications, and examine geographic coverage.Results: As part of the evaluation of the system, we analyzed 778 reports with HealthMap, representing 87 disease categories and 89 countries. The automated classifier performed with 84% accuracy, demonstrating significant usefulness in managing the large volume of information processed by the system. Accuracy for ProMED alerts is 91% compared to Google News reports at 81%, as ProMED messages follow a more regular structure.Conclusion: HealthMap is a useful free and open resource employing text-processing algorithms to identify important disease outbreak information through a user-friendly interface. pubtype: Academic Journal doctype: pictorial tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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