Enhancing clinical name entity recognition based on hybrid deep learning scheme

Robert Phan; Thoai Luu; Rachel Davey; Girija Chetty

doi:10.1109/ICDMW.2019.00153

Enhancing clinical name entity recognition based on hybrid deep learning scheme

Robert Phan, Thoai Luu, Rachel Davey, Girija Chetty

Research output: A Conference proceeding or a Chapter in Book › Conference contribution › peer-review

4 Citations (Scopus)

Abstract

This paper describes a novel machine learning approach based on deeper and wider deep learning model, for better feature learning and latent feature discovery for the clinical name entity recognition task. The performance evaluation of the proposed framework with a benchmark clinical NLP dataset, the clinical CLEF eHealth challenge 2016 dataset, has led to promising performance, when assessed in terms of F-measure, Recall and Precision. The Hybrid CNN model with hyperparameter optimization led to an F-score 89 % for the CLEF eHealth 2016 Challenge task involving synthetic nursing handover dataset.

Original language	English
Title of host publication	Proceedings - 19th IEEE International Conference on Data Mining Workshops, ICDMW 2019
Editors	Panagiotis Papapetrou, Xueqi Cheng, Qing He
Place of Publication	United States
Publisher	IEEE, Institute of Electrical and Electronics Engineers
Pages	1049-1055
Number of pages	7
ISBN (Electronic)	9781728146034
ISBN (Print)	9781728148977
DOIs	https://doi.org/10.1109/ICDMW.2019.00153
Publication status	Published - 8 Nov 2019
Event	19th IEEE International Conference on Data Mining Workshops - Beijing, China Duration: 8 Nov 2019 → 11 Nov 2019

Publication series

Name	IEEE International Conference on Data Mining Workshops, ICDMW
Volume	2019-November
ISSN (Print)	2375-9232
ISSN (Electronic)	2375-9259

Workshop

Workshop	19th IEEE International Conference on Data Mining Workshops
Abbreviated title	ICDMW 2019
Country/Territory	China
City	Beijing
Period	8/11/19 → 11/11/19

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10.1109/ICDMW.2019.00153

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Phan, R., Luu, T., Davey, R., & Chetty, G. (2019). Enhancing clinical name entity recognition based on hybrid deep learning scheme. In P. Papapetrou, X. Cheng, & Q. He (Eds.), Proceedings - 19th IEEE International Conference on Data Mining Workshops, ICDMW 2019 (pp. 1049-1055). [8955534] (IEEE International Conference on Data Mining Workshops, ICDMW; Vol. 2019-November). IEEE, Institute of Electrical and Electronics Engineers. https://doi.org/10.1109/ICDMW.2019.00153

Phan, Robert ; Luu, Thoai ; Davey, Rachel et al. / Enhancing clinical name entity recognition based on hybrid deep learning scheme. Proceedings - 19th IEEE International Conference on Data Mining Workshops, ICDMW 2019. editor / Panagiotis Papapetrou ; Xueqi Cheng ; Qing He. United States : IEEE, Institute of Electrical and Electronics Engineers, 2019. pp. 1049-1055 (IEEE International Conference on Data Mining Workshops, ICDMW).

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title = "Enhancing clinical name entity recognition based on hybrid deep learning scheme",

abstract = "This paper describes a novel machine learning approach based on deeper and wider deep learning model, for better feature learning and latent feature discovery for the clinical name entity recognition task. The performance evaluation of the proposed framework with a benchmark clinical NLP dataset, the clinical CLEF eHealth challenge 2016 dataset, has led to promising performance, when assessed in terms of F-measure, Recall and Precision. The Hybrid CNN model with hyperparameter optimization led to an F-score 89 % for the CLEF eHealth 2016 Challenge task involving synthetic nursing handover dataset.",

keywords = "Convolutional neural networks, Deep learning, Feedforward networks, Hyperparameter optimization, Machine learning, Optimization algorithm, Recurrent neural networks",

author = "Robert Phan and Thoai Luu and Rachel Davey and Girija Chetty",

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booktitle = "Proceedings - 19th IEEE International Conference on Data Mining Workshops, ICDMW 2019",

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note = "19th IEEE International Conference on Data Mining Workshops, ICDMW 2019 ; Conference date: 08-11-2019 Through 11-11-2019",

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Phan, R, Luu, T, Davey, R & Chetty, G 2019, Enhancing clinical name entity recognition based on hybrid deep learning scheme. in P Papapetrou, X Cheng & Q He (eds), Proceedings - 19th IEEE International Conference on Data Mining Workshops, ICDMW 2019., 8955534, IEEE International Conference on Data Mining Workshops, ICDMW, vol. 2019-November, IEEE, Institute of Electrical and Electronics Engineers, United States, pp. 1049-1055, 19th IEEE International Conference on Data Mining Workshops, Beijing, China, 8/11/19. https://doi.org/10.1109/ICDMW.2019.00153

Enhancing clinical name entity recognition based on hybrid deep learning scheme. / Phan, Robert; Luu, Thoai; Davey, Rachel et al.
Proceedings - 19th IEEE International Conference on Data Mining Workshops, ICDMW 2019. ed. / Panagiotis Papapetrou; Xueqi Cheng; Qing He. United States: IEEE, Institute of Electrical and Electronics Engineers, 2019. p. 1049-1055 8955534 (IEEE International Conference on Data Mining Workshops, ICDMW; Vol. 2019-November).

Research output: A Conference proceeding or a Chapter in Book › Conference contribution › peer-review

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KW - Convolutional neural networks

KW - Deep learning

KW - Feedforward networks

KW - Hyperparameter optimization

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KW - Optimization algorithm

KW - Recurrent neural networks

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Phan R, Luu T, Davey R , Chetty G. Enhancing clinical name entity recognition based on hybrid deep learning scheme. In Papapetrou P, Cheng X, He Q, editors, Proceedings - 19th IEEE International Conference on Data Mining Workshops, ICDMW 2019. United States: IEEE, Institute of Electrical and Electronics Engineers. 2019. p. 1049-1055. 8955534. (IEEE International Conference on Data Mining Workshops, ICDMW). doi: 10.1109/ICDMW.2019.00153

Enhancing clinical name entity recognition based on hybrid deep learning scheme

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