RealMedDial: A Real Telemedical Dialogue Dataset Collected from Online Chinese Short-Video Clips

Bo Xu, Hongtong Zhang, Jian Wang, Xiaokun Zhang, Dezhi Hao, Linlin Zong, Hongfei Lin, Fenglong Ma


Abstract
Intelligent medical services have attracted great research interests for providing automated medical consultation. However, the lack of corpora becomes a main obstacle to related research, particularly data from real scenarios. In this paper, we construct RealMedDial, a Chinese medical dialogue dataset based on real medical consultation. RealMedDial contains 2,637 medical dialogues and 24,255 utterances obtained from Chinese short-video clips of real medical consultations. We collected and annotated a wide range of meta-data with respect to medical dialogue including doctor profiles, hospital departments, diseases and symptoms for fine-grained analysis on language usage pattern and clinical diagnosis. We evaluate the performance of medical response generation, department routing and doctor recommendation on RealMedDial. Results show that RealMedDial are applicable to a wide range of NLP tasks with respect to medical dialogue.
Anthology ID:
2022.coling-1.295
Volume:
Proceedings of the 29th International Conference on Computational Linguistics
Month:
October
Year:
2022
Address:
Gyeongju, Republic of Korea
Venue:
COLING
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Publisher:
International Committee on Computational Linguistics
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Pages:
3342–3352
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URL:
https://aclanthology.org/2022.coling-1.295
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Cite (ACL):
Bo Xu, Hongtong Zhang, Jian Wang, Xiaokun Zhang, Dezhi Hao, Linlin Zong, Hongfei Lin, and Fenglong Ma. 2022. RealMedDial: A Real Telemedical Dialogue Dataset Collected from Online Chinese Short-Video Clips. In Proceedings of the 29th International Conference on Computational Linguistics, pages 3342–3352, Gyeongju, Republic of Korea. International Committee on Computational Linguistics.
Cite (Informal):
RealMedDial: A Real Telemedical Dialogue Dataset Collected from Online Chinese Short-Video Clips (Xu et al., COLING 2022)
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https://aclanthology.org/2022.coling-1.295.pdf