Evidence map›Paper›PMID 31438244›Full record

ArticleStudies in health technology and informatics2019

Named Entity Recognition in Prehospital Trauma Care.

Greg M Silverman, Elizabeth A Lindemann, Geetanjali Rajamani, Raymond L Finzel, Reed McEwan, Benjamin C Knoll, Serguei Pakhomov, Genevieve B Melton, Christopher J Tignanelli

Abstract read
PubMed Full text at PMC Publisher
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 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Use of artificial intelligence to support prehospital traumatic injury care: A scoping review.Journal of the American College of Emergency Physicians open · 2024
    Article
  3. 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

9 authors.

Greg M SilvermanAcademic Health Center - Information Systems, University of Minnesota, Minneapolis, Minnesota, USA.
Elizabeth A LindemannDepartment of Surgery, University of Minnesota, Minneapolis, Minnesota, USA.
Geetanjali RajamaniStanford University, Stanford, CA, USA.
Raymond L FinzelCollege of Pharmacy, University of Minnesota, Minneapolis, Minnesota, USA.
Reed McEwanAcademic Health Center - Information Systems, University of Minnesota, Minneapolis, Minnesota, USA.
Benjamin C KnollInstitute for Health Informatics, University of Minnesota, Minneapolis, Minnesota, USA.
Serguei PakhomovCollege of Pharmacy, University of Minnesota, Minneapolis, Minnesota, USA.
Genevieve B MeltonInstitute for Health Informatics, University of Minnesota, Minneapolis, Minnesota, USA.
Christopher J TignanelliInstitute for Health Informatics, University of Minnesota, Minneapolis, Minnesota, USA.

Funding

University of Minnesota Clinical and Translational Science Institute (UMN CTSI)UL1TR002494 · NCATS · UNIVERSITY OF MINNESOTA · PI BLAZAR, BRUCE R, WEISDORF, DANIEL J · 2018 to 2022
$34.9M
Open Health Natural Language Processing CollaboratoryU01TR002062 · NCATS · MAYO CLINIC ROCHESTER · PI JIANG, XIAOQIAN, LIU, HONGFANG · 2017 to 2021
$7.6M
Innovative Methods for Real-time Risk Modeling of Postoperative ComplicationsR01GM120079 · NIGMS · UNIVERSITY OF MINNESOTA · PI SIMON, GYORGY · 2017 to 2020
$2.1M
AHRQ HHS R01 HS022085AHRQ HHS R01 HS024532NCATS NIH HHS U01 TR002062NCATS NIH HHS UL1 TR002494NIGMS NIH HHS R01 GM120079
6 · The paper itself

Abstract

Natural language processing (NLP) methods would improve outcomes in the area of prehospital Emergency Medical Services (EMS) data collection and abstraction. This study evaluated off-the-shelf solutions for automating labelling of clinically relevant data from EMS reports. A qualitative approach for choosing the best possible ensemble of pretrained NLP systems was developed and validated along with a feature using word embeddings to test phrase synonymy. The ensemble showed increased performance over individual systems.

Indexed as

Emergency Medical ServicesNatural Language ProcessingEmergency medical servicesLabelingNatural language processing

Identifiers

PMID31438244
PMCPMC7360018

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

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.