Evidence map›Paper›PMID 31438189›Full record

ArticleStudies in health technology and informatics2019

Patient-Pivoted Automated Trial Eligibility Pipeline: The First of Three Phases in a Modular Architecture.

Paul M Heider, Stéphane M Meystre

Abstract read
In one paragraph

Article in Studies in health technology and informatics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. Observational
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

2 authors.

Paul M HeiderBiomedical Informatics Center, Medical University of South Carolina, Charleston, South Carolina, USA.
Stéphane M MeystreBiomedical Informatics Center, Medical University of South Carolina, Charleston, South Carolina, USA.

Funding

Translational Science Laboratory Shared ResourceP30CA138313 · NCI · MEDICAL UNIVERSITY OF SOUTH CAROLINA · PI RAYMOND N. DUBOIS · 2009 to 2026
$42.7M
South Carolina Clinical & Translational Research Institute (SCTR)UL1TR001450 · NCATS · MEDICAL UNIVERSITY OF SOUTH CAROLINA · PI BRADY, KATHLEEN T., FLUME, PATRICK A · 2015 to 2024
$41.1M
NCATS NIH HHS UL1 TR001450NCI NIH HHS P30 CA138313
6 · The paper itself

Abstract

Automated extraction of patient trial eligibility for clinical research studies can increase enrollment at a decreased time and money cost. We have developed a modular trial eligibility pipeline including patient-batched processing and an internal webservice backed by a uimaFIT pipeline as part of a multi-phase approach to include note-batched processing, the ability to query trials matching patients or patients matching trials, and an external alignment engine to connect patients to trials.

Indexed as

Eligibility DeterminationCosts and Cost AnalysisHumansPatient SelectionEligibility DeterminationMachine LearningNatural Language Processing

Identifiers

PMID31438189
PMCPMC6944198

What OpenQuestion holds

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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.