Knowledge Automation in Online Medical Inquiry Platforms
Zhao, Yifei1; Wang, Feiyue1; Wang, Jing1; Shi, Xiaobo2
2016
Conference Namethe INFORMS International 2016 Annual Meeting
Source PublicationProceedings of the INFORMS International 2016 Annual Meeting
Conference Date2016
Conference PlaceWaikoloa Village, Hawaii, USA
Abstractnone; Internet inquiry platforms have bloomed into the supplement and optimization of the traditional medical service systems over the past few years. Due to the lack of intelligence, the platforms cannot deal with medical knowledge automatically, usually resulting poor user experience. In this paper, we try to realize knowledge automation on internet inquiry platforms, from the following aspects: we use retrieval models combining word embedding and query likelihood language models to recommend similar cases for users from the semantic perspective; we use classification techniques to determine the quality of answers, and optimize the answers for the current query by finding a better one or changing some words in the original one; word embedding is integrated into some medical rules to help achieve automatic triage; more scientific semi automatic triage with user interaction is also tried; we also recommend suitable patients for doctors and recommend suitable doctors for patients through some recommendation technologies, expecting better user experience. Experimental results on the large-scale real world internet inquiry platform data show that our work can improve the platforms significantly.
KeywordNone
Indexed ByEI
Document Type会议论文
Identifierhttp://ir.ia.ac.cn/handle/173211/11710
Collection复杂系统管理与控制国家重点实验室_先进控制与自动化
Corresponding AuthorZhao, Yifei
Affiliation1.Institute of Automation, Chinese Academy of Sciences
2.Qingdao Academy of Intelligent Industries
Recommended Citation
GB/T 7714
Zhao, Yifei,Wang, Feiyue,Wang, Jing,et al. Knowledge Automation in Online Medical Inquiry Platforms[C],2016.
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