MedDialog: Two Large-scale Medical Dialogue Datasets

• DOI: 10.48550/arxiv.2004.03329
• Publication Date: 2020-01-01
• Authors: He, Xuehai; Chen, Shu; Ju, Zeqian; Dong, Xiangyu; Fang, Hongchao; Wang, Sicheng; Yang, Yue; Zeng, Jiaqi; Zhang, Ruisi; Zhang, Ruoyu; Zhou, Meng; Zhu, Penghui; Xie, Pengtao
• Keywords: FOS: Computer and information sciences; Computer Science - Machine Learning; Computer Science - Computation and Language; Computer Science - Artificial Intelligence; Machine Learning (stat.ML); 02 engineering and technology; 3. Good health; Machine Learning (cs.LG); Artificial Intelligence (cs.AI); Statistics - Machine Learning; 0202 electrical engineering, electronic engineering, information engineering; Computation and Language (cs.CL)

Medical dialogue systems are promising in assisting in telemedicine to increase access to healthcare services, improve the quality of patient care, and reduce medical costs. To facilitate the research and development of medical dialogue systems, we build two large-scale medical dialogue datasets: MedDialog-EN and MedDialog-CN. MedDialog-EN is an English dataset containing 0.3 million conversations between patients and doctors and 0.5 million utterances. MedDialog-CN is an Chinese dataset containing 1.1 million conversations and 4 million utterances. To our best knowledge, MedDialog-(EN,CN) are the largest medical dialogue datasets to date. The dataset is available at https://github.com/UCSD-AI4H/Medical-Dialogue-System