期刊论文、会议论文

He, Tingting（何婷婷）

英文

BMC Medical Informatics and Decision Making

1472-6947

2019

19

9

251

International Conference on Intelligent Computing (ICIC) / Intelligent Computing and Biomedical Informatics (ICBI) Conference - Medical Informatics and Decision Making

AUG 15-18, 2018

PEOPLES R CHINA

[Pan, Min;Sun, Bo] Cent China Normal Univ, Natl Engn Res Ctr E Learning, Wuhan 430079, Hubei, Peoples R China.^[Pan, Min] Hubei Normal Univ, Sch Comp & Informat Engn, Huangshi 435002, Hubei, Peoples R China.^[Zhang, Yue;Zhu, Qiang;He, Tingting;Jiang, Xingpeng] Cent China Normal Univ, Sch Comp, Wuhan 430079, Hubei, Peoples R China.

CAMPUS, 4 CRINAN ST, LONDON N1 9XW, ENGLAND

BMC

10.1186/s12911-019-0986-6

This research is supported by the Fundamental Research Funds for Central Universities (CCNU18JCK05), the National Natural Science Foundation of China (61532008), the National Science Foundation of China (61572223), and National Key Research and Development Program of China (2017YFC0909502). Publication costs have been funded by the National Key Research and Development Program of China (2017YFC0909502). We are very grateful to the anonymous reviewers and deputy editors for their valuable and excellent comments, which have greatly improved the quality of this paper.

本校为第一且通讯机构

BACKGROUND: In order to better help doctors make decision in the clinical setting, research is necessary to connect electronic health record (EHR) with the biomedical literature. Pseudo Relevance Feedback (PRF) is a kind of classical query modification technique that has shown to be effective in many retrieval models and thus suitable for handling terse language and clinical jargons in EHR. Previous work has introduced a set of constraints (axioms) of traditional PRF model. However, in the feedback document, the importance degree of candidate term and the co-occurrence relationship between a c...