Task-oriented Dialogue System for Automatic Diagnosis

Zhongyu Wei, Qianlong Liu, Baolin Peng, Huaixiao Tou, Ting Chen, Xuanjing Huang, Kam-fai Wong, Xiangying Dai


Abstract
In this paper, we make a move to build a dialogue system for automatic diagnosis. We first build a dataset collected from an online medical forum by extracting symptoms from both patients’ self-reports and conversational data between patients and doctors. Then we propose a task-oriented dialogue system framework to make diagnosis for patients automatically, which can converse with patients to collect additional symptoms beyond their self-reports. Experimental results on our dataset show that additional symptoms extracted from conversation can greatly improve the accuracy for disease identification and our dialogue system is able to collect these symptoms automatically and make a better diagnosis.
Anthology ID:
P18-2033
Volume:
Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)
Month:
July
Year:
2018
Address:
Melbourne, Australia
Editors:
Iryna Gurevych, Yusuke Miyao
Venue:
ACL
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
201–207
Language:
URL:
https://aclanthology.org/P18-2033
DOI:
10.18653/v1/P18-2033
Bibkey:
Cite (ACL):
Zhongyu Wei, Qianlong Liu, Baolin Peng, Huaixiao Tou, Ting Chen, Xuanjing Huang, Kam-fai Wong, and Xiangying Dai. 2018. Task-oriented Dialogue System for Automatic Diagnosis. In Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers), pages 201–207, Melbourne, Australia. Association for Computational Linguistics.
Cite (Informal):
Task-oriented Dialogue System for Automatic Diagnosis (Wei et al., ACL 2018)
Copy Citation:
PDF:
https://aclanthology.org/P18-2033.pdf
Poster:
 P18-2033.Poster.pdf