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Bilingual term alignment from comparable corpora in English discharge summary and Chinese discharge summary

Overview of attention for article published in BMC Bioinformatics, May 2015
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Title
Bilingual term alignment from comparable corpora in English discharge summary and Chinese discharge summary
Published in
BMC Bioinformatics, May 2015
DOI 10.1186/s12859-015-0606-0
Pubmed ID
Authors

Yan Xu, Luoxin Chen, Junsheng Wei, Sophia Ananiadou, Yubo Fan, Yi Qian, Eric I-Chao Chang, Junichi Tsujii

Abstract

Electronic medical record (EMR) systems have become widely used throughout the world to improve the quality of healthcare and the efficiency of hospital services. A bilingual medical lexicon of Chinese and English is needed to meet the demand for the multi-lingual and multi-national treatment. We make efforts to extract a bilingual lexicon from English and Chinese discharge summaries with a small seed lexicon. The lexical terms can be classified into two categories: single-word terms (SWTs) and multi-word terms (MWTs). For SWTs, we use a label propagation (LP; context-based) method to extract candidates of translation pairs. For MWTs, which are pervasive in the medical domain, we propose a term alignment method, which firstly obtains translation candidates for each component word of a Chinese MWT, and then generates their combinations, from which the system selects a set of plausible translation candidates. We compare our LP method with a baseline method based on simple context-similarity. The LP based method outperforms the baseline with the accuracies: 4.44% Acc1, 24.44% Acc10, and 62.22% Acc100, where AccN means the top N accuracy. The accuracy of the LP method drops to 5.41% Acc10 and 8.11% Acc20 for MWTs. Our experiments show that the method based on term alignment improves the performance for MWTs to 16.22% Acc10 and 27.03% Acc20. We constructed a framework for building an English-Chinese term dictionary from discharge summaries in the two languages. Our experiments have shown that the LP-based method augmented with the term alignment method will contribute to reduction of manual work required to compile a bilingual sydictionary of clinical terms.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 39 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 1 3%
Unknown 38 97%

Demographic breakdown

Readers by professional status Count As %
Student > Master 9 23%
Researcher 8 21%
Student > Ph. D. Student 6 15%
Other 2 5%
Lecturer 2 5%
Other 6 15%
Unknown 6 15%
Readers by discipline Count As %
Computer Science 13 33%
Medicine and Dentistry 5 13%
Linguistics 3 8%
Social Sciences 3 8%
Mathematics 2 5%
Other 6 15%
Unknown 7 18%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 2. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 10 May 2015.
All research outputs
#13,942,329
of 22,803,211 outputs
Outputs from BMC Bioinformatics
#4,470
of 7,281 outputs
Outputs of similar age
#133,573
of 263,982 outputs
Outputs of similar age from BMC Bioinformatics
#81
of 127 outputs
Altmetric has tracked 22,803,211 research outputs across all sources so far. This one is in the 37th percentile – i.e., 37% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,281 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.4. This one is in the 35th percentile – i.e., 35% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 263,982 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 48th percentile – i.e., 48% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 127 others from the same source and published within six weeks on either side of this one. This one is in the 32nd percentile – i.e., 32% of its contemporaries scored the same or lower than it.