Paper Info
Title
BeCAS: biomedical concept recognition services and visualization.
Abstract
The continuous growth of the biomedical scientific literature has been motivating the development of text-mining tools able to efficiently process all this information. Although numerous domain-specific solutions are available, there is no web-based concept-recognition system that combines the ability to select multiple concept types to annotate, to reference external databases and to automatically annotate nested and intercepted concepts. BeCAS, the Biomedical Concept Annotation System, is an API for biomedical concept identification and a web-based tool that addresses these limitations. MEDLINE abstracts or free text can be annotated directly in the web interface, where identified concepts are enriched with links to reference databases. Using its customizable widget, it can also be used to augment external web pages with concept highlighting features. Furthermore, all text-processing and annotation features are made available through an HTTP REST API, allowing integration in any text-processing pipeline.
Year
DOI
Venue
2013
10.1093/bioinformatics/btt317
BIOINFORMATICS
Field
DocType
Volume
Data mining,Scientific literature,World Wide Web,Annotation,Information retrieval,Web page,Computer science,Visualization,Concept recognition,Bioinformatics,MEDLINE
Journal
29
Issue
ISSN
Citations 
15
1367-4803
26
PageRank 
References 
Authors
0.96
9
4
Name
Order
Citations
PageRank
Tiago Nunes1261.30
David Campos221910.69
Sérgio Matos341529.51
José Luis Oliveira476084.03