Clinical Text Classification in Cancer Real-World Data in Spanish

Author:

Moreno-Barea Francisco J.ORCID,Mesa HéctorORCID,Ribelles NuriaORCID,Alba EmilioORCID,Jerez José M.ORCID

Publisher

Springer Nature Switzerland

Reference33 articles.

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2. Baker, S., Korhonen, A., Pyysalo, S.: Cancer hallmark text classification using convolutional neural networks. In: Proceedings of the 5th Workshop on Building and Evaluating Resources for Biomedical Text Mining (BioTxtM), pp. 1–9 (2016)

3. Bojanowski, P., Grave, E., Joulin, A., Mikolov, T.: Enriching word vectors with subword information. Trans. Assoc. Comput. Linguist. 5, 135–146 (2017). https://doi.org/10.1162/tacl_a_00051

4. Chen, T., Guestrin, C.: Xgboost: a scalable tree boosting system. In: Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 785–794 (2016). https://doi.org/10.1145/2939672.2939785

5. Chung, J., Gulcehre, C., Cho, K., Bengio, Y.: Empirical evaluation of gated recurrent neural networks on sequence modeling. In: NIPS 2014 Workshop on Deep Learning, December 2014 (2014)

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