Evidence map›Paper›PMID 31841150›Full record

ArticleJournal of the American Medical Informatics Association : JAMIA2020

Advancing the state of the art in automatic extraction of adverse drug events from narratives.

Özlem Uzuner, Amber Stubbs, Leslie Lenert

Abstract readEditorial
In one paragraph

Article in Journal of the American Medical Informatics Association : JAMIA, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing 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

9 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Clinical concept extraction using transformers.Journal of the American Medical Informatics Association : JAMIA · 2020
    Article
  8. Article
  9. A learning pharmacy practice enabled by the pharmacists' patient care process.Journal of the American Pharmacists Association : JAPhA
    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

3 authors.

Özlem UzunerDepartment of Information Sciences and Technology, George Mason University, Fairfax, Virginia, USA.
Amber StubbsDivision of Mathematics, Computing, and Statistics, Simmons University, Boston, Massachusetts, USA.
Leslie LenertDepartment of Medicine, Medical College of South Carolina, Charleston, South Carolina, USA.

Funding

National NLP Clinical Challenges (n2c2): Challenges in Natural Language Processing for Clinical NarrativesR13LM013127 · NLM · GEORGE MASON UNIVERSITY · PI UZUNER, OZLEM · 2019 to 2023
$100k
Challenges in Natural Language Processing in Clinical TextR13LM011411 · NLM · STATE UNIVERSITY OF NEW YORK AT ALBANY · PI UZUNER, OZLEM · 2012 to 2016
$98k
NLM NIH HHS R13 LM011411NLM NIH HHS R13 LM013127
6 · The paper itself

Abstract

PubMed holds no abstract for this paper.

Indexed as

Drug-Related Side Effects and Adverse ReactionsMedical RecordsNatural Language ProcessingElectronic Health RecordsHumansInformation Storage and RetrievalNarration

Identifiers

PMID31841150
PMCPMC6913224

What OpenQuestion holds

Textmetadata
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.