Evidence map›Paper›PMID 29495428›Full record

ArticleInternational journal of environmental research and public health2018

A Text Structuring Method for Chinese Medical Text Based on Temporal Information.

Runtong Zhang, Fuzhi Chu, Donghua Chen, Xiaopu Shang

Abstract read
In one paragraph

Article in International journal of environmental research and public health, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Runtong ZhangDepartment of Information Management, Beijing Jiaotong University, Beijing 100044, China. rtzhang@bjtu.edu.cn.ORCID 0000-0003-0246-5058
Fuzhi ChuDepartment of Information Management, Beijing Jiaotong University, Beijing 100044, China. october_chu@163.com.
Donghua ChenDepartment of Information Management, Beijing Jiaotong University, Beijing 100044, China. chendonghua@bjtu.edu.cn.
Xiaopu ShangDepartment of Information Management, Beijing Jiaotong University, Beijing 100044, China. sxp@bjtu.edu.cn.ORCID 0000-0002-7872-5744

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Chinese Electronic Medical Records (EMRs) contains a large number of complex medical free text which includes a variety of information, such as temporal information, patients' symptoms and laboratory data. However, as an important knowledge base, these unstructured text data in EMR are hard to process directly by computer to support further medical research. This paper proposes a novel text structuring method to extract knowledge from EMR texts and reorganize them in chronological order according to the temporal information in the text. By implementing some entropy-based algorithms as contrast, experiments evaluate the performance of the proposed method, which indicates the new method can significantly reduce the complexity of EMR text. This work is significant in structuring the EMR free text into temporal-structured data for further medical analysis.

Indexed as

Electronic Health RecordsLanguageAlgorithmsChinaHumansInformation Storage and RetrievalTime FactorsChineseelectronic medical recordsinformation entropytemporal informationtext structuring method

Identifiers

PMID29495428
PMCPMC5876947

What OpenQuestion holds

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LicenceCC BY
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.