Evidence map›Paper›PMID 28096894›Full record

ArticleComputational and mathematical methods in medicine2016

A Novel Sample Selection Strategy for Imbalanced Data of Biomedical Event Extraction with Joint Scoring Mechanism.

Yang Lu, Xiaolei Ma, Yinan Lu, Yuxin Zhou, Zhili Pei

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Computational and mathematical methods in medicine, 2016. 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

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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. Review
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

5 authors.

Yang LuCollege of Computer Science and Technology, Jilin University, Changchun, Jilin 130000, China; Library, Inner Mongolia University for Nationalities, Tongliao, Inner Mongolia 028000, China.
Xiaolei MaCollege of Computer Science and Technology, Jilin University, Changchun, Jilin 130000, China; Library, Inner Mongolia University for Nationalities, Tongliao, Inner Mongolia 028000, China.
Yinan LuCollege of Computer Science and Technology, Jilin University, Changchun, Jilin 130000, China.ORCID 0000-0001-5786-9178
Yuxin ZhouCollege of Computer Science and Technology, Jilin University, Changchun, Jilin 130000, China.
Zhili PeiCollege of Computer Science and Technology, Inner Mongolia University for Nationalities, Tongliao, Inner Mongolia 028000, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Biomedical event extraction is an important and difficult task in bioinformatics. With the rapid growth of biomedical literature, the extraction of complex events from unstructured text has attracted more attention. However, the annotated biomedical corpus is highly imbalanced, which affects the performance of the classification algorithms. In this study, a sample selection algorithm based on sequential pattern is proposed to filter negative samples in the training phase. Considering the joint information between the trigger and argument of multiargument events, we extract triplets of multiargument events directly using a support vector machine classifier. A joint scoring mechanism, which is based on sentence similarity and importance of trigger in the training data, is used to correct the predicted results. Experimental results indicate that the proposed method can extract events efficiently.

Indexed as

Severity of Illness IndexAlgorithmsComputational BiologyData MiningDiseaseGene Expression RegulationHumansModels, StatisticalNatural Language ProcessingNeoplasmsPattern Recognition, AutomatedReproducibility of ResultsSupport Vector Machine

Identifiers

PMID28096894
PMCPMC5206857

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.