A Joint Model of Clinical Domain Classification and Slot Filling Based on RCNN and BiGRU-CRF

Yuming Li; Pin Ni; Junkun Peng; Jiayi Zhu; Zhenjin Dai; Gangmin Li; Xuming Bai

doi:10.1109/BigData47090.2019.9005449

A Joint Model of Clinical Domain Classification and Slot Filling Based on RCNN and BiGRU-CRF

Yuming Li, Pin Ni, Junkun Peng, Jiayi Zhu, Zhenjin Dai, Gangmin Li, Xuming Bai

Xi'an Jiaotong-Liverpool University

Research output: Chapter in Book or Report/Conference proceeding › Conference Proceeding › peer-review

12 Citations (Scopus)

Abstract

The task of the Intent Classification Slot Filling serves as a key joint task in the voice assistant, which also plays the role of the pre-work in the construction of the medical consultation assistant system. How to distribute a doctor-patient conversation into a formatted electronic medical record to an accurate department (Intent Classification) to extract the key named entities or mentions (Slot Filling) through a specialized domain knowledge recognizer is one of the key steps of the entire system. In real cases, the medical vocabulary and clinical entities in different departments of the hospital often differ to some extent. Therefore, we propose a comprehensive model based on CMed-BERT, RCNN and BiGRU-CRF for a joint task of department identification and slot filling of the specific domain. Experimental results confirmed the competitiveness of our model.

Original language	English
Title of host publication	Proceedings - 2019 IEEE International Conference on Big Data, Big Data 2019
Editors	Chaitanya Baru, Jun Huan, Latifur Khan, Xiaohua Tony Hu, Ronay Ak, Yuanyuan Tian, Roger Barga, Carlo Zaniolo, Kisung Lee, Yanfang Fanny Ye
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	6133-6135
Number of pages	3
ISBN (Electronic)	9781728108582
DOIs	https://doi.org/10.1109/BigData47090.2019.9005449
Publication status	Published - Dec 2019
Event	2019 IEEE International Conference on Big Data, Big Data 2019 - Los Angeles, United States Duration: 9 Dec 2019 → 12 Dec 2019

Publication series

Name	Proceedings - 2019 IEEE International Conference on Big Data, Big Data 2019

Conference

Conference	2019 IEEE International Conference on Big Data, Big Data 2019
Country/Territory	United States
City	Los Angeles
Period	9/12/19 → 12/12/19

Keywords

BiGRU-CRF
CMed-BERT
NER
RCNN

Access to Document

10.1109/BigData47090.2019.9005449

Cite this

Li, Y., Ni, P., Peng, J., Zhu, J., Dai, Z., Li, G., & Bai, X. (2019). A Joint Model of Clinical Domain Classification and Slot Filling Based on RCNN and BiGRU-CRF. In C. Baru, J. Huan, L. Khan, X. T. Hu, R. Ak, Y. Tian, R. Barga, C. Zaniolo, K. Lee, & Y. F. Ye (Eds.), Proceedings - 2019 IEEE International Conference on Big Data, Big Data 2019 (pp. 6133-6135). Article 9005449 (Proceedings - 2019 IEEE International Conference on Big Data, Big Data 2019). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/BigData47090.2019.9005449

Li, Yuming ; Ni, Pin ; Peng, Junkun et al. / A Joint Model of Clinical Domain Classification and Slot Filling Based on RCNN and BiGRU-CRF. Proceedings - 2019 IEEE International Conference on Big Data, Big Data 2019. editor / Chaitanya Baru ; Jun Huan ; Latifur Khan ; Xiaohua Tony Hu ; Ronay Ak ; Yuanyuan Tian ; Roger Barga ; Carlo Zaniolo ; Kisung Lee ; Yanfang Fanny Ye. Institute of Electrical and Electronics Engineers Inc., 2019. pp. 6133-6135 (Proceedings - 2019 IEEE International Conference on Big Data, Big Data 2019).

@inproceedings{002240964bfe4bfebc4f8c3eef2a0982,

title = "A Joint Model of Clinical Domain Classification and Slot Filling Based on RCNN and BiGRU-CRF",

abstract = "The task of the Intent Classification Slot Filling serves as a key joint task in the voice assistant, which also plays the role of the pre-work in the construction of the medical consultation assistant system. How to distribute a doctor-patient conversation into a formatted electronic medical record to an accurate department (Intent Classification) to extract the key named entities or mentions (Slot Filling) through a specialized domain knowledge recognizer is one of the key steps of the entire system. In real cases, the medical vocabulary and clinical entities in different departments of the hospital often differ to some extent. Therefore, we propose a comprehensive model based on CMed-BERT, RCNN and BiGRU-CRF for a joint task of department identification and slot filling of the specific domain. Experimental results confirmed the competitiveness of our model.",

keywords = "BiGRU-CRF, CMed-BERT, NER, RCNN",

author = "Yuming Li and Pin Ni and Junkun Peng and Jiayi Zhu and Zhenjin Dai and Gangmin Li and Xuming Bai",

note = "Funding Information: V. ACKNOWLEDGEMENT This work is partially supported by the AI University Research Centre (AI-URC) through XJTLU Key Programme Special Fund (KSF-P-02) and KSF-A-17. And it is also partially supported by Suzhou Science and Technology Programme Key Industrial Technology Innovation programme with project code SYG201840. We appreciate their support and guidance. Publisher Copyright: {\textcopyright} 2019 IEEE.; 2019 IEEE International Conference on Big Data, Big Data 2019 ; Conference date: 09-12-2019 Through 12-12-2019",

year = "2019",

month = dec,

doi = "10.1109/BigData47090.2019.9005449",

language = "English",

series = "Proceedings - 2019 IEEE International Conference on Big Data, Big Data 2019",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

pages = "6133--6135",

editor = "Chaitanya Baru and Jun Huan and Latifur Khan and Hu, {Xiaohua Tony} and Ronay Ak and Yuanyuan Tian and Roger Barga and Carlo Zaniolo and Kisung Lee and Ye, {Yanfang Fanny}",

booktitle = "Proceedings - 2019 IEEE International Conference on Big Data, Big Data 2019",

}

Li, Y, Ni, P, Peng, J, Zhu, J, Dai, Z, Li, G & Bai, X 2019, A Joint Model of Clinical Domain Classification and Slot Filling Based on RCNN and BiGRU-CRF. in C Baru, J Huan, L Khan, XT Hu, R Ak, Y Tian, R Barga, C Zaniolo, K Lee & YF Ye (eds), Proceedings - 2019 IEEE International Conference on Big Data, Big Data 2019., 9005449, Proceedings - 2019 IEEE International Conference on Big Data, Big Data 2019, Institute of Electrical and Electronics Engineers Inc., pp. 6133-6135, 2019 IEEE International Conference on Big Data, Big Data 2019, Los Angeles, United States, 9/12/19. https://doi.org/10.1109/BigData47090.2019.9005449

A Joint Model of Clinical Domain Classification and Slot Filling Based on RCNN and BiGRU-CRF. / Li, Yuming; Ni, Pin; Peng, Junkun et al.
Proceedings - 2019 IEEE International Conference on Big Data, Big Data 2019. ed. / Chaitanya Baru; Jun Huan; Latifur Khan; Xiaohua Tony Hu; Ronay Ak; Yuanyuan Tian; Roger Barga; Carlo Zaniolo; Kisung Lee; Yanfang Fanny Ye. Institute of Electrical and Electronics Engineers Inc., 2019. p. 6133-6135 9005449 (Proceedings - 2019 IEEE International Conference on Big Data, Big Data 2019).

Research output: Chapter in Book or Report/Conference proceeding › Conference Proceeding › peer-review

TY - GEN

T1 - A Joint Model of Clinical Domain Classification and Slot Filling Based on RCNN and BiGRU-CRF

AU - Li, Yuming

AU - Ni, Pin

AU - Peng, Junkun

AU - Zhu, Jiayi

AU - Dai, Zhenjin

AU - Li, Gangmin

AU - Bai, Xuming

N1 - Funding Information: V. ACKNOWLEDGEMENT This work is partially supported by the AI University Research Centre (AI-URC) through XJTLU Key Programme Special Fund (KSF-P-02) and KSF-A-17. And it is also partially supported by Suzhou Science and Technology Programme Key Industrial Technology Innovation programme with project code SYG201840. We appreciate their support and guidance. Publisher Copyright: © 2019 IEEE.

PY - 2019/12

Y1 - 2019/12

N2 - The task of the Intent Classification Slot Filling serves as a key joint task in the voice assistant, which also plays the role of the pre-work in the construction of the medical consultation assistant system. How to distribute a doctor-patient conversation into a formatted electronic medical record to an accurate department (Intent Classification) to extract the key named entities or mentions (Slot Filling) through a specialized domain knowledge recognizer is one of the key steps of the entire system. In real cases, the medical vocabulary and clinical entities in different departments of the hospital often differ to some extent. Therefore, we propose a comprehensive model based on CMed-BERT, RCNN and BiGRU-CRF for a joint task of department identification and slot filling of the specific domain. Experimental results confirmed the competitiveness of our model.

AB - The task of the Intent Classification Slot Filling serves as a key joint task in the voice assistant, which also plays the role of the pre-work in the construction of the medical consultation assistant system. How to distribute a doctor-patient conversation into a formatted electronic medical record to an accurate department (Intent Classification) to extract the key named entities or mentions (Slot Filling) through a specialized domain knowledge recognizer is one of the key steps of the entire system. In real cases, the medical vocabulary and clinical entities in different departments of the hospital often differ to some extent. Therefore, we propose a comprehensive model based on CMed-BERT, RCNN and BiGRU-CRF for a joint task of department identification and slot filling of the specific domain. Experimental results confirmed the competitiveness of our model.

KW - BiGRU-CRF

KW - CMed-BERT

KW - NER

KW - RCNN

UR - http://www.scopus.com/inward/record.url?scp=85081298159&partnerID=8YFLogxK

U2 - 10.1109/BigData47090.2019.9005449

DO - 10.1109/BigData47090.2019.9005449

M3 - Conference Proceeding

AN - SCOPUS:85081298159

T3 - Proceedings - 2019 IEEE International Conference on Big Data, Big Data 2019

SP - 6133

EP - 6135

BT - Proceedings - 2019 IEEE International Conference on Big Data, Big Data 2019

A2 - Baru, Chaitanya

A2 - Huan, Jun

A2 - Khan, Latifur

A2 - Hu, Xiaohua Tony

A2 - Ak, Ronay

A2 - Tian, Yuanyuan

A2 - Barga, Roger

A2 - Zaniolo, Carlo

A2 - Lee, Kisung

A2 - Ye, Yanfang Fanny

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 2019 IEEE International Conference on Big Data, Big Data 2019

Y2 - 9 December 2019 through 12 December 2019

ER -

Li Y, Ni P, Peng J, Zhu J, Dai Z, Li G et al. A Joint Model of Clinical Domain Classification and Slot Filling Based on RCNN and BiGRU-CRF. In Baru C, Huan J, Khan L, Hu XT, Ak R, Tian Y, Barga R, Zaniolo C, Lee K, Ye YF, editors, Proceedings - 2019 IEEE International Conference on Big Data, Big Data 2019. Institute of Electrical and Electronics Engineers Inc. 2019. p. 6133-6135. 9005449. (Proceedings - 2019 IEEE International Conference on Big Data, Big Data 2019). doi: 10.1109/BigData47090.2019.9005449

A Joint Model of Clinical Domain Classification and Slot Filling Based on RCNN and BiGRU-CRF

Abstract

Publication series

Conference

Keywords

Access to Document

Other files and links

Fingerprint

Cite this