Semi-automatic semantic annotation of PubMed queries: a study on quality, efficiency, satisfaction.
about
Crowdsourcing in biomedicine: challenges and opportunitiesPubMed and beyond: a survey of web tools for searching biomedical literaturetmChem: a high performance approach for chemical named entity recognition and normalizationChemical-induced disease relation extraction with various linguistic featuresAuDis: an automatic CRF-enhanced disease normalization in biomedical textAssessing the state of the art in biomedical relation extraction: overview of the BioCreative V chemical-disease relation (CDR) taskBioCreative V CDR task corpus: a resource for chemical disease relation extractionAutomatic extraction of drug indications from FDA drug labelsLabeledIn: cataloging labeled indications for human drugsNCBI disease corpus: a resource for disease name recognition and concept normalizationBiocuration workflows and text mining: overview of the BioCreative 2012 Workshop Track IICommunity challenges in biomedical text mining over 10 years: success, failure and the future.Developing topic-specific search filters for PubMed with click-through data.MeSH Now: automatic MeSH indexing at PubMed scale via learning to rankChemical-induced disease relation extraction via convolutional neural network.BioC interoperability track overviewtmBioC: improving interoperability of text-mining tools with BioC.BC4GO: a full-text corpus for the BioCreative IV GO task.Overview of the gene ontology task at BioCreative IVAssisted annotation of medical free text using RapTAT.Accelerating literature curation with text-mining tools: a case study of using PubTator to curate genes in PubMed abstracts.A study on PubMed search tag usage pattern: association rule mining of a full-day PubMed query log.tmVar: a text mining approach for extracting sequence variants in biomedical literature.Predicting clicks of PubMed articles.Scaling drug indication curation through crowdsourcing.Analysis of PubMed User Sessions Using a Full-Day PubMed Query Log: A Comparison of Experienced and Nonexperienced PubMed Users.Discovering biomedical semantic relations in PubMed queries for information retrieval and database curationSimConcept: a hybrid approach for simplifying composite named entities in biomedical textCoIN: a network analysis for document triageA survey on annotation tools for the biomedical literature.Evaluating the impact of pre-annotation on annotation speed and potential bias: natural language processing gold standard development for clinical named entity recognition in clinical trial announcements.PheKnow-Cloud: A Tool for Evaluating High-Throughput Phenotype Candidates using Online Medical Literature.Biomedical text mining for research rigor and integrity: tasks, challenges, directions.Towards PubMed 2.0.OC-2-KB: integrating crowdsourcing into an obesity and cancer knowledge base curation systemA document level neural model integrated domain knowledge for chemical-induced disease relations
P2860
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P2860
Semi-automatic semantic annotation of PubMed queries: a study on quality, efficiency, satisfaction.
description
2010 nî lūn-bûn
@nan
2010 թուականի Նոյեմբերին հրատարակուած գիտական յօդուած
@hyw
2010 թվականի նոյեմբերին հրատարակված գիտական հոդված
@hy
2010年の論文
@ja
2010年論文
@yue
2010年論文
@zh-hant
2010年論文
@zh-hk
2010年論文
@zh-mo
2010年論文
@zh-tw
2010年论文
@wuu
name
Semi-automatic semantic annota ...... ity, efficiency, satisfaction.
@ast
Semi-automatic semantic annota ...... ity, efficiency, satisfaction.
@en
type
label
Semi-automatic semantic annota ...... ity, efficiency, satisfaction.
@ast
Semi-automatic semantic annota ...... ity, efficiency, satisfaction.
@en
prefLabel
Semi-automatic semantic annota ...... ity, efficiency, satisfaction.
@ast
Semi-automatic semantic annota ...... ity, efficiency, satisfaction.
@en
P2860
P1476
Semi-automatic semantic annota ...... ity, efficiency, satisfaction.
@en
P2093
Rezarta Islamaj Doğan
Zhiyong Lu
P2860
P304
P356
10.1016/J.JBI.2010.11.001
P577
2010-11-20T00:00:00Z