Integrating image caption information into biomedical document classification in support of biocuration
Author(s) -
Xiangying Jiang,
Pengyuan Li,
James A. Kadin,
Judith A. Blake,
Martin Ringwald,
Hagit Shatkay
Publication year - 2020
Publication title -
database
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.406
H-Index - 62
ISSN - 1758-0463
DOI - 10.1093/database/baaa024
Subject(s) - computer science , information retrieval , classifier (uml) , document classification , precision and recall , biological database , pipeline (software) , classification scheme , data curation , annotation , data science , world wide web , artificial intelligence , bioinformatics , biology , programming language
Gathering information from the scientific literature is essential for biomedical research, as much knowledge is conveyed through publications. However, the large and rapidly increasing publication rate makes it impractical for researchers to quickly identify all and only those documents related to their interest. As such, automated biomedical document classification attracts much interest. Such classification is critical in the curation of biological databases, because biocurators must scan through a vast number of articles to identify pertinent information within documents most relevant to the database. This is a slow, labor-intensive process that can benefit from effective automation.
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