Machine learning for biomedical literature triage.
Ontology highlight
ABSTRACT:
SUBMITTER: Almeida H
PROVIDER: S-EPMC4281078 | biostudies-literature | 2014
REPOSITORIES: biostudies-literature
Publications
Machine learning for biomedical literature triage.
Almeida Hayda H Meurs Marie-Jean MJ Kosseim Leila L Butler Greg G Tsang Adrian A
PloS one 20141231 12
This paper presents a machine learning system for supporting the first task of the biological literature manual curation process, called triage. We compare the performance of various classification models, by experimenting with dataset sampling factors and a set of features, as well as three different machine learning algorithms (Naive Bayes, Support Vector Machine and Logistic Model Trees). The results show that the most fitting model to handle the imbalanced datasets of the triage classificati ...[more]
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