https://doi.org/10.7490/f1000research.1116340.1
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Zientala P, Szpakowski M and Cozzi M. A highly scalable, efficient approach to biomedical information extraction using data augmentation, transfer learning and BiLSTM-CNN [version 1; not peer reviewed]. F1000Research 2018, 7:1903 (poster) (https://doi.org/10.7490/f1000research.1116340.1)
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A highly scalable, efficient approach to biomedical information extraction using data augmentation, transfer learning and BiLSTM-CNN

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Published 07 Dec 2018

A highly scalable, efficient approach to biomedical information extraction using data augmentation, transfer learning and BiLSTM-CNN

[version 1; not peer reviewed]

Author Affiliations
1 Researchably, Inc., USA
Presented at
WeCNLP 2018
Abstract
Competing Interests

No competing interests were disclosed

Keywords
information extraction, NLP, biomedical, data augmentation, transfer learning, machine learning
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