A LSTM-Based Method with Attention Mechanism for Adverse Drug Reaction Sentences Detection
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Publisher
Springer International Publishing
Link
http://link.springer.com/content/pdf/10.1007/978-3-030-36664-3_3
Reference24 articles.
1. Ji, Y., Ying, H., Dews, P., Mansour, A., Tran, J., Miller, R.E., Massanari, R.M.: A potential causal association mining algorithm for screening adverse drug reactions in postmarketing surveillance. IEEE Trans. Inf. Technol. Biomed. 15(3), 428–437 (2011). https://doi.org/10.1109/titb.2011.2131669
2. Harpaz, R., Callahan, A., Tamang, S., Low, Y., Odgers, D., Finlayson, S., Jung, K., LePendu, P., Shah, N.H.: Text mining for adverse drug events: the promise, challenges, and state of the art. Drug Saf. 37(10), 777–790 (2014). https://doi.org/10.1007/s40264-014-0218-z
3. Segura-Bedmar, I., Martínez, P.: Pharmacovigilance through the development of text mining and natural language processing techniques. J. Biomed. Inf. 58, 288–291 (2015). https://doi.org/10.1016/j.jbi.2015.11.001
4. Demner-Fushman, D., Shooshan, S.E., Rodriguez, L., Aronson, A.R., Lang, F., Rogers, W., Roberts, K., Tonning, J.: A dataset of 200 structured product labels annotated for adverse drug reactions. Sci. Data 5(180), 001 (2018). https://doi.org/10.1038/sdata.2018.1
5. Gurulingappa, H., Rajput, A.M., Roberts, A., Fluck, J., Hofmann-Apitius, M., Toldo, L.: Development of a benchmark corpus to support the automatic extraction of drug-related adverse effects from medical case reports. J. Biomed. Inf. 45, 885–892 (2012). https://doi.org/10.1016/j.jbi.2012.04.008
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