Evidence map›Paper›PMID 37393610›Full record

ArticleSTAR protocols2023

Protocol for the automatic extraction of epidemiological information via a pre-trained language model.

Zhizheng Wang, Xiao Fan Liu, Zhanwei Du, Lin Wang, Ye Wu, Petter Holme, Michael Lachmann, Hongfei Lin, Zhuoyue Wang, Yu Cao and 3 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in STAR protocols, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

13 authors.

Zhizheng WangCollege of Computer Science and Technology, Dalian University of Technology, 116023, Dalian, Liaoning, China.
Xiao Fan LiuWeb Mining Laboratory, Department of Media and Communication, City University of Hong Kong, Kowloon Tong, Hong Kong Special Administrative Region, 999077, China.
Zhanwei DuWHO Collaborating Centre for Infectious Disease Epidemiology and Control, School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Central And Western District, Hong Kong Special Administrative Region, 999077, China.
Lin WangDepartment of Genetics, University of Cambridge, Cambridge CB2 3EH, UK.
Ye WuComputational Communication Research Center and School of Journalism and Communication, Beijing Normal University, Beijing 100091, China.
Petter HolmeTokyo Tech World Research Hub Initiative (WRHI), Institute of Innovative Research, Tokyo Institute of Technology, Tokyo 152-8550, Japan.
Michael LachmannSanta Fe Institute, Santa Fe, NM 87507, USA.
Hongfei LinCollege of Computer Science and Technology, Dalian University of Technology, 116023, Dalian, Liaoning, China.
Zhuoyue WangCollege of Computer Science and Technology, Dalian University of Technology, 116023, Dalian, Liaoning, China.
Yu CaoCollege of Computer Science and Technology, Dalian University of Technology, 116023, Dalian, Liaoning, China.
Zoie S Y WongGraduate School of Public Health, St. Luke's International University, Tokyo 104-0044, Japan. Electronic address: zoiesywong@gmail.com.
Xiao-Ke XuComputational Communication Research Center, Beijing Normal University, Zhuhai, Guangdong, 519087, China; School of Journalism and Communication, Beijing Normal University, Beijing, 100875, China. Electronic address: xuxiaoke@foxmail.com.
Yuanyuan SunCollege of Computer Science and Technology, Dalian University of Technology, 116023, Dalian, Liaoning, China. Electronic address: syuan@dlut.edu.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The lack of systems to automatically extract epidemiological fields from open-access COVID-19 cases restricts the timeliness of formulating prevention measures. Here we present a protocol for using CCIE, a COVID-19 Cases Information Extraction system based on the pre-trained language model.

Indexed as

COVID-19Natural Language ProcessingHumansLanguageClinical ProtocolComputer SciencesHealth Sciences

Identifiers

PMID37393610
PMCPMC10328978

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.