Deep Learning Based Biomedical NER Framework

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Abstract

This paper describes a novel deep learning-based framework for biomedical name entity recognition. Bio-Entity name entity recognition task based on three different deep learning techniques: Feedforward Networks (FFNs), Recurrent Neural Networks (RNNs), and Hybrid Convolutional Neural Networks (CNNs), has allowed better latent feature learning and discovery for the complex NLP task. The performance evaluation of the proposed framework with the BioNLP dataset corresponding to biomedical entity recognition task, has led to promising performance, when assessed in terms of F-measure, Recall and Precision. The best performing deep learner based on Hybrid CNN approach has resulted in an F-score of 70.32%, and surpassed the performance reported by other participants in the Challenge task.

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Phan, R., Luu, T. M., Davey, R., & Chetty, G. (2018). Deep Learning Based Biomedical NER Framework. In Proceedings of the 2018 IEEE Symposium Series on Computational Intelligence, SSCI 2018 (pp. 33–40). Institute of Electrical and Electronics Engineers Inc. https://doi.org/10.1109/SSCI.2018.8628740

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