Bar charts detection and analysis in biomedical literature of PubMed Central.
AMIA Annu Symp Proc
; 2017: 859-865, 2017.
Article
em En
| MEDLINE
| ID: mdl-29854152
ABSTRACT
Bar charts are crucial to summarize and present multi-faceted data sets in biomedical publications. Quantitative information carried by bar charts is of great interest to scientists and practitioners, which make it valuable to parse bar charts. This fact together with the abundance of bar chart images and their shared common patterns gives us a good candidates for automated image mining and parsing. We demonstrate a workflow to analyze bar charts and give a few feasible solutions to apply it. We are able to detect bar segments and panels with a promising performance in terms of both accuracy and recall, and we also perform extensive experiments to identify the entities of bar charts in the images of biomedical literature collected from PubMed Central. While we cannot provide a complete instance of the application using our method, we present evidence that this kind of image mining is feasible.
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Algoritmos
/
Modelos Estatísticos
/
Bases de Dados como Assunto
/
PubMed
/
Mineração de Dados
Tipo de estudo:
Diagnostic_studies
/
Risk_factors_studies
Idioma:
En
Ano de publicação:
2017
Tipo de documento:
Article