PhenoCHF Corpus PhenoCHF is an annotated corpus consisting of documents belonging to two different text types (i.e., narrative reports from electronic health records (EHRs) and literature articles). It is manually annotated by medical doctors with detailed information relating to mentions of phenotype concepts and disease-phenotype relations. Distribution Availability
Available - Restricted Use
Licence CC - BY
Restrictions: Attribution
User Nature: Academic, Commercial
Download location: hidden
Distribution Access/Medium: Downloadable
Attribution Details: a) The annotations in HIMERA were created by the National Centre for Text Mining (NaCTeM). Please attribute NaCTeM, and also cite the following article(s), depending on which types of annotations are used:
Entity Annotations -
Alnazzawi, N., Thompson, P., Batista-Navarro, R. and Ananiadou, S.. (2015). Using text mining techniques to extract phenotypic information from the PhenoCHF corpus. BMC Medical Informatics and Decision Making, 15(Suppl. 2): S3;
Normalisation Annotations -
Noha Alnazzawi, Paul Thompson and Sophia Ananiadou (2016). Mapping Phenotypic Information in Heterogeneous Textual Sources to a Domain-Specific Terminological Resource. PLOS ONE;
Relation Annotations
Alnazzawi, N., Thompson, P. and Ananiadou, S.. (2014). Building a semantically annotated corpus for congestive heart and renal failure from clinical records and the literature. In Proceedings of the 5th International Workshop on Health Text Mining and Information Analysis (Louhi), pp. 69-74;
Distribution rights holders:
IPR Holder
Contact Person
Monolingual text corpus Languages
English
Linguality Linguality type: Monolingual
Size Character encoding
UTF - 8
Domains
Narrative clinical records
Conforms to Other
biomedical literature
Conforms to Other
Modalities Classification Congestive Heart Falilure (CHF)
(10 Texts)
Text type: Academic articles
Register: Formal
Text genre: Biomedical text
Congestive Heart Falilure (CHF)
(300 Texts)
Text type: Discharge summaries
Register: Informal
Text genre: Narrative clinical records
Resource Creation Metadata Created: 10/08/2016
Last Updated: 10/08/2016
Metadata Language:
English
(en)
Usage Foreseen Use Nlp Applications Use NLP Specific: Annotation, Entity Mention Recognition, Event Extraction, Information Extraction, Knowledge Discovery, Lexicon Enhancement, Named Entity Recognition, Text Mining
Actual Use - Nlp Applications Use NLP Specific: Event Extraction, Named Entity Recognition, Text Mining
Documentation Tool Documentation: Manual, Online
Document Type: Article
Alnazzawi, N., Thompson, P., Batista-Navarro, R. and Ananiadou, S.,
Using text mining techniques to extract phenotypic information from the PhenoCHF corpus http://www.biomedcen...
. In: BMC Medical Informatics and Decision Making
15(Suppl. 2)
, pp. S3
, 2015
Document Language:
English
Document Type: Article
Noha Alnazzawi, Paul Thompson and Sophia Ananiadou ,
Mapping Phenotypic Information in Heterogeneous Textual Sources to a Domain-Specific Terminological Resource
Document Type: In Proceedings
Alnazzawi, N., Thompson, P., Batista-Navarro, R. and Ananiadou, S.,
Building a semantically annotated corpus for congestive heart and renal failure from clinical records and the literature http://aclweb.org/an...
, pp. 69-74
, 2014
Book Title: Proceedings of the 5th International Workshop on Health Text Mining and Information Analysis (Louhi
Document Language:
English
Document Type: Manual
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