Machine learning for biomedical literature triage

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 differe...

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Veröffentlicht in:	PloS one 2014-12, Vol.9 (12), p.e115892-e115892
Hauptverfasser:	Almeida, Hayda, Meurs, Marie-Jean, Kosseim, Leila, Butler, Greg, Tsang, Adrian
Format:	Artikel
Sprache:	eng
Schlagworte:	Accuracy Algorithms Analysis Artificial intelligence Bayes Theorem Bayesian analysis Bioinformatics Biological activity Biology and Life Sciences Classification Computer and Information Sciences Computer science Costs Cybernetics Data mining Databases, Bibliographic Datasets Decision making Decision Trees Genomics Health informatics Learning Learning algorithms Lignocellulose Machine learning Medical Informatics - methods Models, Theoretical Research and Analysis Methods Sampling Sampling techniques Software engineering Studies Support Vector Machine Trees
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