---
title: "Task-oriented Dialogue System for Automatic Diagnosis (2018)"
description: "The authors therefore propose a task-oriented dialogue system that asks patients follow-up questions… 22 references, cited by 60 papers here."
authors: ["Zhongyu Wei", "Qianlong Liu", "Baolin Peng", "Huaixiao Tou", "Ting Chen", "Xuanjing Huang", "Kam-fai Wong", "Xiangying Dai"]
year: 2018
venue: "Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)"
source: "https://aclanthology.org/P18-2033/"
doi: "10.18653/v1/p18-2033"
licence: "CC BY 4.0 (ACL Anthology)"
licence_url: "https://creativecommons.org/licenses/by/4.0/"
summary_licence: "Elamur Cosmic License"
canonical: "https://research.elamur.ai/free/en/papers/wei-2018-task-oriented-dialogue-system-automatic/"
---
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# Task-oriented Dialogue System for Automatic Diagnosis

**Authors:** [Zhongyu Wei](https://md.research.elamur.ai/free/en/authors/zhongyu-wei/), Qianlong Liu, [Baolin Peng](https://md.research.elamur.ai/free/en/authors/baolin-peng/), Huaixiao Tou, [Ting Chen](https://md.research.elamur.ai/free/en/authors/ting-chen/), [Xuanjing Huang](https://md.research.elamur.ai/free/en/authors/xuanjing-huang/), [Kam-fai Wong](https://md.research.elamur.ai/free/en/authors/kam-fai-wong/) and Xiangying Dai · **Year:** 2018 · **Venue:** [Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)](https://md.research.elamur.ai/free/en/venues/acl/) ([ACL 2018](https://md.research.elamur.ai/free/en/venues/acl/2018/)) · **Publisher:** [Association for Computational Linguistics](https://md.research.elamur.ai/free/en/publishers/association-for-computational-linguistics/) · **Licence:** [CC BY 4.0 (ACL Anthology)](https://creativecommons.org/licenses/by/4.0/)

**Links:** [Publisher's page](https://aclanthology.org/P18-2033/) · [PDF](https://aclanthology.org/P18-2033.pdf) · [DOI 10.18653/v1/p18-2033](https://doi.org/10.18653/v1/p18-2033) · [OpenAlex](https://openalex.org/W2886305736)

**Citations:** 193 citations (OpenAlex, 2026-10-14) · [60](https://md.research.elamur.ai/free/en/papers/wei-2018-task-oriented-dialogue-system-automatic/cited-by/) in our library, of the 141,840 papers whose bibliographies we read

## Summary
The paper tackles automatic disease diagnosis when a patient's initial description is incomplete. Diagnostic models built on electronic health records are expensive to train and hard to transfer across diseases. The authors therefore propose a task-oriented dialogue system that asks patients follow-up questions to gather more symptoms. They built a Chinese dataset from the pediatric section of an online healthcare platform (Baidu Muzhi). It covers four childhood diseases, and each record pairs a patient's self-report (explicit symptoms) with the doctor–patient conversation (implicit symptoms). Annotators marked symptom spans using BIO tags and recorded whether each symptom was present. Medical experts then mapped the spans to SNOMED CT concepts. The system focuses on the dialogue manager: a user simulator samples user goals from the data, and a DQN policy trained with reinforcement learning decides which symptom to ask about next or which disease to name. Adding implicit symptoms clearly improves classifier accuracy, and the DQN agent beats random and rule-based agents. This shows that conversational symptom collection is a practical route to automatic diagnosis.

## Key points
- **Dataset:** 710 user goals across four diseases: infantile diarrhea (200), children functional dyspepsia (150), upper respiratory infection (160) and children's bronchitis (200).
  - Annotators identified 144 unique normalized symptoms; only the 67 occurring at least 10 times were kept to shrink the action space.
  - Inter-annotator Cohen's kappa was 71% for self-reports and 67% for conversations.
  - The data split is 568 user goals for training and 142 for testing.
- **Value of implicit symptoms:** an SVM using both explicit and implicit symptoms (SVM-ex&im) reached 0.71 overall accuracy, compared with 0.59 for explicit symptoms only (SVM-ex).
- **Dialogue agents on 5K simulated dialogues:**

  | Agent | Success rate | Average reward | Average turns |
  |---|---|---|---|
  | Random | 0.06 | −24.36 | 17.51 |
  | Rule-based | 0.23 | −13.78 | 17.00 |
  | DQN | 0.65 | 20.51 | 5.11 |

  The DQN agent outperforms SVM-ex but still trails SVM-ex&im.
- **Setup:**
  - Dialogues are capped at 22 turns.
  - Rewards are +44 for a correct diagnosis and −22 for a failure, plus a −1 penalty per turn.
  - Natural language understanding and generation use templates.
  - The replay buffer is warm-started with experiences from the rule-based agent.
- **Authorship:** the first author is Qianlong Liu; Zhongyu Wei is the corresponding author. The paper appeared as an ACL 2018 short paper (pp. 201–207), and the authors released the dataset publicly.

*Our summary of the paper, in our own words — not its text. The work belongs to its authors; read it at the links above.*

## Institutions

- [Fudan University](https://md.research.elamur.ai/free/en/universities/fudan-university/) — University, Shanghai, China · 65 works · 19,402 citations
- [Baidu](https://md.research.elamur.ai/free/en/companies/baidu/) — Company, Beijing, China · 40 works · 14,627 citations
- [Chinese University of Hong Kong](https://md.research.elamur.ai/free/en/universities/chinese-university-of-hong-kong/) — University, Hong Kong, China · 53 works · 12,921 citations

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## Cite

Cite as: 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. Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers).

The paper itself, not this page. BibTeX from the library's record of the work.

```bibtex
@inproceedings{wei2018task,
  title = {{Task-oriented Dialogue System for Automatic Diagnosis}},
  author = {Zhongyu Wei, Qianlong Liu, Baolin Peng, Huaixiao Tou, Ting Chen, Xuanjing Huang, Kam-fai Wong and Xiangying Dai},
  booktitle = {Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)},
  year = {2018},
  doi = {10.18653/v1/p18-2033},
  url = {https://doi.org/10.18653/v1/p18-2033}
}
```

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## References

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*Updated 24 October 2026*