Identifying medical terms in patient-authored text: a crowdsourcing-based approach.
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Crowdsourcing in biomedicine: challenges and opportunitiesConsumers' Use of UMLS Concepts on Social Media: Diabetes-Related Textual Data Analysis in Blog and Social Q&A; SitesMining consumer health vocabulary from community-generated textClustering clinical trials with similar eligibility criteria featuresInduced lexico-syntactic patterns improve information extraction from online medical forumsEnriching consumer health vocabulary through mining a social Q&A site: A similarity-based approach.Leveraging cues from person-generated health data for peer matching in online communities.Managing free text for secondary use of health data.Characterization of Temporal Semantic Shifts of Peer-to-Peer Communication in a Health-Related Online Community: Implications for Data-driven Health Promotion.Crowdsourcing black market prices for prescription opioids.Characterizing the sublanguage of online breast cancer forums for medications, symptoms, and emotions.Opportunity costs of reward delays and the discounting of hypothetical money and cigarettesAspiring to Unintended Consequences of Natural Language Processing: A Review of Recent Developments in Clinical and Consumer-Generated Text Processing.VisOHC: Designing Visual Analytics for Online Health CommunitiesAutomatically Detecting Failures in Natural Language Processing Tools for Online Community Text.In Pursuit of Theoretical Ground in Behavior Change Support Systems: Analysis of Peer-to-Peer Communication in a Health-Related Online CommunityIs the crowd better as an assistant or a replacement in ontology engineering? An exploration through the lens of the Gene OntologyUsing Nonexperts for Annotating Pharmacokinetic Drug-Drug Interaction Mentions in Product Labeling: A Feasibility Study.Consumers' Patient Portal Preferences and Health Literacy: A Survey Using Crowdsourcing.Content-specific network analysis of peer-to-peer communication in an online community for smoking cessationHealth-Related Coping and Social Interaction in People with Multiple Sclerosis Supported by a Social Network: Pilot Study With a New Methodological ApproachReply & Supply: Efficient crowdsourcing when workers do more than answer questions.Comparing Amazon's Mechanical Turk Platform to Conventional Data Collection Methods in the Health and Medical Research Literature.Reconciliation of patient/doctor vocabulary in a structured resource.Talking About My Care: Detecting Mentions of Hormonal Therapy Adherence Behavior in an Online Breast Cancer Community.Mapping of Crowdsourcing in Health: Systematic Review.
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P2860
Identifying medical terms in patient-authored text: a crowdsourcing-based approach.
description
article científic
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article scientifique
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articolo scientifico
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artigo científico
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bilimsel makale
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scientific article published on 05 May 2013
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vedecký článok
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vetenskaplig artikel
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videnskabelig artikel
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vědecký článek
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name
Identifying medical terms in patient-authored text: a crowdsourcing-based approach.
@en
Identifying medical terms in patient-authored text: a crowdsourcing-based approach.
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type
label
Identifying medical terms in patient-authored text: a crowdsourcing-based approach.
@en
Identifying medical terms in patient-authored text: a crowdsourcing-based approach.
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prefLabel
Identifying medical terms in patient-authored text: a crowdsourcing-based approach.
@en
Identifying medical terms in patient-authored text: a crowdsourcing-based approach.
@nl
P2860
P1476
Identifying medical terms in patient-authored text: a crowdsourcing-based approach.
@en
P2093
Diana Lynn MacLean
Jeffrey Heer
P2860
P304
P356
10.1136/AMIAJNL-2012-001110
P577
2013-05-05T00:00:00Z