Large-scale biomedical concept recognition: an evaluation of current automatic annotators and their parameters
about
KneeTex: an ontology-driven system for information extraction from MRI reportsThe Implicitome: A Resource for Rationalizing Gene-Disease AssociationsGene Ontology synonym generation rules lead to increased performance in biomedical concept recognition.Text mining resources for the life sciences.Exploring the Unexplored: Identifying Implicit and Indirect Descriptions of Biomedical Terminologies Based on Multifaceted Weighting CombinationsThe role of ontologies in biological and biomedical research: a functional perspectiveTen Simple Rules for Experiments' ProvenanceOntology-based annotations and semantic relations in large-scale (epi)genomics dataMapping biological entities using the longest approximately common prefix method.Finding pathway-modulating genes from a novel Ontology Fingerprint-derived gene networkAssociating disease-related genetic variants in intergenic regions to the genes they impactNOBLE - Flexible concept recognition for large-scale biomedical natural language processingGeneration of silver standard concept annotations from biomedical texts with special relevance to phenotypes.Supporting the annotation of chronic obstructive pulmonary disease (COPD) phenotypes with text mining workflows.Assessing the impact of case sensitivity and term information gain on biomedical concept recognition.Concept selection for phenotypes and diseases using learn to rankSORTA: a system for ontology-based re-coding and technical annotation of biomedical phenotype data.Semantic biomedical resource discovery: a Natural Language Processing framework.JuFiT: A Configurable Rule Engine for Filtering and Generating New Multilingual Umls Terms.Coreference resolution improves extraction of Biological Expression Language statements from texts.Knowledge Representation and Management. From Ontology to Annotation. Findings from the Yearbook 2015 Section on Knowledge Representation and Management.Evaluating a variety of text-mined features for automatic protein function prediction with GOstructRecognition of chemical entities: combining dictionary-based and grammar-based approaches.Training and evaluation corpora for the extraction of causal relationships encoded in biological expression language (BEL).Semantic annotation in biomedicine: the current landscape.A new synonym-substitution method to enrich the human phenotype ontology.A collaborative filtering based approach to biomedical knowledge discovery.Entity recognition in the biomedical domain using a hybrid approach.Improving precision in concept normalization.Biotea: semantics for Pubmed Central.PubCaseFinder: A Case-Report-Based, Phenotype-Driven Differential-Diagnosis System for Rare DiseasesKnowledge-based biomedical Data ScienceGene ontology concept recognition using named concept: understanding the various presentations of the gene functions in biomedical literatureSIFR annotator: ontology-based semantic annotation of French biomedical text and clinical notes
P2860
Q24288846-43310863-C1DD-4E42-B930-B569008A4EE2Q27061916-30C71C7B-5BC1-40F3-8ED2-28C30DCB5069Q27321359-3574A215-FD21-4850-ADEF-864092FE85B3Q28076577-3B2DD64E-42F5-4462-831C-BDDC49835E89Q28595527-50E03057-C97D-4601-81FB-719E90FF0947Q28607224-3E35AC22-2248-4504-B51B-5BDF4B13FEE3Q28974685-6939C39F-4809-41B6-A105-59A944EDBC64Q31090008-ED962CDF-9908-4881-A75C-1E81AFF7C1ECQ33863069-DB4483FB-A3EF-40BE-9700-63F97FE41879Q34312936-4B01F403-D37D-4E9E-B7BA-FAFD5DF4F5A7Q34440951-B2ABBE9E-E03B-460E-AD1D-DBE3568806B6Q34508872-8FCAAA45-129E-433A-8E6A-403C2A420479Q34994898-CD93951C-CE23-4DCD-8B56-1261AF2E9A8DQ35190720-51928865-ADE0-43D0-A9B8-44476909023AQ35195431-A952FD35-4579-45A0-826F-724659C56682Q35669850-0BD75F08-6387-4B20-8C57-1BA1059E73CBQ35780898-FD448673-7FF1-4916-911B-252F5EB5AB6EQ35794224-4F91FCE8-BDCB-4EBB-A4C6-985B4B5F4A69Q36613395-835EF72E-2B62-4179-90C4-83191984F2D2Q37060122-6D6F4ED1-044F-4B6B-8A28-63C8FFEFE6DBQ38405576-C0E82FBD-106D-4872-ADCF-6FB075602B88Q38411006-2372AA9A-7C64-4EA4-B531-39AC1B5C3610Q38414273-2F6D0BB6-FB2C-4F5C-9978-A85272F6CD5FQ38443558-688064E7-9840-4AE0-A3EF-781481970E29Q42362959-82E5C160-49AD-47EC-84DD-075945275939Q42374536-282CFFDA-31C0-43EA-B2D2-D396D06FB569Q42696227-14F944E7-AB2A-4DA6-A8AA-02F8E566212AQ45944039-124728F5-0EE0-4D5A-B8D5-B5C53CBE944BQ47143867-C3B47A37-6954-4346-81B9-94FA4FDD1F27Q47191940-33D7EAC1-0312-4C8A-9D5A-0FF782B658DCQ56887528-680F2208-E6B3-4B9E-A3B7-93F0B2B672FAQ57001498-6F662243-BBD3-448F-8C1D-8697CA0B915EQ58132499-0C353B8D-11FB-45DF-8354-02A3ADEF34C5Q58605223-2D4740A3-CDEF-449B-A51D-A62FD8048FE4
P2860
Large-scale biomedical concept recognition: an evaluation of current automatic annotators and their parameters
description
2014 nî lūn-bûn
@nan
2014 թուականի Փետրուարին հրատարակուած գիտական յօդուած
@hyw
2014 թվականի փետրվարին հրատարակված գիտական հոդված
@hy
2014年の論文
@ja
2014年論文
@yue
2014年論文
@zh-hant
2014年論文
@zh-hk
2014年論文
@zh-mo
2014年論文
@zh-tw
2014年论文
@wuu
name
Large-scale biomedical concept ...... nnotators and their parameters
@ast
Large-scale biomedical concept ...... nnotators and their parameters
@en
Large-scale biomedical concept ...... nnotators and their parameters
@nl
type
label
Large-scale biomedical concept ...... nnotators and their parameters
@ast
Large-scale biomedical concept ...... nnotators and their parameters
@en
Large-scale biomedical concept ...... nnotators and their parameters
@nl
prefLabel
Large-scale biomedical concept ...... nnotators and their parameters
@ast
Large-scale biomedical concept ...... nnotators and their parameters
@en
Large-scale biomedical concept ...... nnotators and their parameters
@nl
P2093
P2860
P50
P3181
P356
P1433
P1476
Large-scale biomedical concept ...... nnotators and their parameters
@en
P2093
Christophe Roeder
Christopher Funk
K Bretonnel Cohen
Michael Bada
William Baumgartner
P2860
P2888
P3181
P356
10.1186/1471-2105-15-59
P407
P577
2014-02-26T00:00:00Z
P5875
P6179
1034420642