Evidence map›Paper›PMID 26262333›Full record

ArticleStudies in health technology and informatics2015

A Frequency-based Strategy of Obtaining Sentences from Clinical Data Repository for Crowdsourcing.

Dingcheng Li, Majid Rastegar Mojarad, Yanpeng Li, Sunghwan Sohn, Saeed Mehrabi, Ravikumar Komandur Elayavilli, Yue Yu, Hongfang Liu

Abstract read
PubMed Full text at PMC
In one paragraph

Article in Studies in health technology and informatics, 2015. 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. Clinical Data Warehousing: A Scoping Review.Journal of the Society for Clinical Data Management · 2024
    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

8 authors.

Dingcheng LiMayo Clinic, Rochester, MN, USA.
Majid Rastegar MojaradMayo Clinic, Rochester, MN, USA.
Yanpeng LiMayo Clinic, Rochester, MN, USA.
Sunghwan SohnMayo Clinic, Rochester, MN, USA.
Saeed MehrabiMayo Clinic, Rochester, MN, USA.
Ravikumar Komandur ElayavilliMayo Clinic, Rochester, MN, USA.
Yue YuMayo Clinic, Rochester, MN, USA.
Hongfang LiuMayo Clinic, Rochester, MN, USA.

Funding

Semi-structured Information Retrieval in Clinical Text for Cohort IdentificationR01LM011934 · NLM · UNIVERSITY OF TEXAS HLTH SCI CTR HOUSTON · PI HERSH, WILLIAM R, LIU, HONGFANG · 2014 to 2025
$5.1M
Methods for generalized ontology terms enrichment analysisR01LM011369 · NLM · STANFORD UNIVERSITY · PI SHAH, NIGAM H · 2013 to 2020
$5.0M
Natural language processing for clinical and translational researchR01GM102282 · NIGMS · MAYO CLINIC ROCHESTER · PI LIU, HONGFANG, PAKHOMOV, SERGUEI VS · 2013 to 2016
$2.5M
Patient Medical History Representation, Extraction, and Inference from EHR DataR01LM011829 · NLM · UNIVERSITY OF TEXAS HLTH SCI CTR HOUSTON · PI TAO, CUI · 2014 to 2018
$1.7M
NIGMS NIH HHS R01 GM102282NIGMS NIH HHS R01GM102282NLM NIH HHS R01 LM011369NLM NIH HHS R01 LM011829NLM NIH HHS R01 LM011934NLM NIH HHS R01LM11369NLM NIH HHS R01LM11829
6 · The paper itself

Abstract

In clinical NLP, one major barrier to adopting crowdsourcing for NLP annotation is the issue of confidentiality for protected health information (PHI) in clinical narratives. In this paper, we investigated the use of a frequency-based approach to extract sentences without PHI. Our approach is based on the assumption that sentences appearing frequently tend to contain no PHI. Both manual and automatic evaluations on 500 sentences out of the 7.9 million sentences of frequencies higher than one show that no PHI can be found among them. The promising results provide potentials of releasing those sentences for obtaining sentence-level NLP annotations via crowdsourcing.

Indexed as

Data Interpretation, StatisticalMachine LearningNatural Language ProcessingSemanticsCrowdsourcingElectronic Health RecordsLanguageMinnesotaPattern Recognition, AutomatedTerminology as TopicVocabulary, Controlled

Identifiers

PMID26262333
PMCPMC5859924

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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.