Document Detail


PatientsLikeMe: Consumer health vocabulary as a folksonomy.
MedLine Citation:
PMID:  18999004     Owner:  NLM     Status:  MEDLINE    
Abstract/OtherAbstract:
PatientsLikeMe is an online social networking community. Subcommunities center on three diagnoses: Amyotrophic Lateral Sclerosis, Multiple Sclerosis and Parkinsons Disease. Community members can describe their symptoms online in natural language, resulting in folksonomic tags available for clinical analysis and for browsing by other users to find patients like me. Forty-three percent of PatientsLikeMe symptom terms are present as exact (24%) or synonymous (19%) terms in the Unified Medical Language System Metathesaurus (National Library of Medicine; 2007AC). Slightly more than half of the symptom terms either do not match the UMLS, or are unclassifiable. A clinical vocabulary, SNOMED CT, accounts for 93% of the matching terms. Analysis of the failed matches reveals challenges for online patient communication, not only with healthcare professionals, but with other patients. In a Web 2.0 environment with lowered barriers between consumers and professionals, a deficiency in knowledge representation affects not only professionals, but consumers as well.
Authors:
Catherine Arnott Smith; Paul J Wicks
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Publication Detail:
Type:  Journal Article     Date:  2008-11-06
Journal Detail:
Title:  AMIA ... Annual Symposium proceedings / AMIA Symposium. AMIA Symposium     Volume:  -     ISSN:  1942-597X     ISO Abbreviation:  AMIA Annu Symp Proc     Publication Date:  2008  
Date Detail:
Created Date:  2008-11-12     Completed Date:  2010-01-08     Revised Date:  2013-06-04    
Medline Journal Info:
Nlm Unique ID:  101209213     Medline TA:  AMIA Annu Symp Proc     Country:  United States    
Other Details:
Languages:  eng     Pagination:  682-6     Citation Subset:  IM    
Affiliation:
University of Wisconsin-Madison, Cambridge, MA, USA.
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MeSH Terms
Descriptor/Qualifier:
Algorithms
Artificial Intelligence
Blogging / organization & administration*
Consumer Health Information / organization & administration*
Consumer Organizations / organization & administration
Internet*
Natural Language Processing*
Pattern Recognition, Automated / methods
Social Support*
Subject Headings*
United States
User-Computer Interface*
Vocabulary, Controlled*
Comments/Corrections

From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine


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