Qing Qian
Peking Union Medical College
6 Papers
12 Citations
Qing Qian is an academic researcher from Peking Union Medical College. The author has contributed to research in topics: Physician Data Query & Computer science. The author has an hindex of 2, co-authored 6 publications.
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Papers
PMO: A knowledge representation model towards precision medicine
TL;DR: This work proposed a semi-automated method which improved the original Ontology Development 101 method to build the Precision Medicine Ontology (PMO), including defining the scope of the PMO according to the definition of PM, collecting terms from different biomedical resources, integrating and normalizing the terms by a combination of machine and manual work.
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ECCParaCorp: a cross-lingual parallel corpus towards cancer education, dissemination and application
Hetong Ma,Feihong Yang,Jiansong Ren,Ni Li,Min Dai,Xuwen Wang,An Fang,Jiao Li,Qing Qian,Jie He +9 more
TL;DR: ECCParaCorp is a parallel corpus focused on cancer in a cross-lingual form, which would make up the imbalance of scarce multilingual corpus resources, bridge the gap between human readable information and machine understanding data resources, and contribute to intelligent technology application as a preparatory data foundation.
RCorp: a resource for chemical disease semantic extraction in Chinese
TL;DR: The result analysis of the corpus proves its quality for the combination therapy related knowledge discovery task and would be a useful resource for the modelling of entity recognition and relation extraction tools.
TBench: A Collaborative Work Platform for Multilingual Terminology Editing and Development.
TL;DR: TBench (Termilology Workbench) is a web-service Java tool consisting of two main functionalities that are knowledge construction and collaborative control in order to achieve custom extensions, reuse, multilingual alignment, integration and refactoring.
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RCorp: a Resource for Chemical Disease Semantic Extration in Chinese
Yueping Sun,Li Hou,Lu Qin,Jiao Li,Qing Qian +4 more
- 10 Jun 2019
TL;DR: The construction work of a corpus for chemical disease semantic extraction in Chinese (RCorp) from a collection of Chinese biomedical abstracts is described, which proves the quality of the corpus for the combination therapy of chronic diseases knowledge discovery task.
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