Abstract
This paper evaluates the impact of various event extraction systems on automatic pathway curation using the popular mTOR pathway. We quantify the impact of training data sets as well as different machine learning classifiers and show that some improve the quality of automatically extracted pathways.
Cite
CITATION STYLE
Kusa, W., & Spranger, M. (2017). External Evaluation of Event Extraction Classifiers for Automatic Pathway Curation: An extended study of the mTOR pathway. In BioNLP 2017 - SIGBioMed Workshop on Biomedical Natural Language Processing, Proceedings of the 16th BioNLP Workshop (pp. 247–256). Association for Computational Linguistics (ACL). https://doi.org/10.18653/v1/w17-2331
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