Evidence map›Paper›PMID 29016825›Full record

ArticleJournal of the American Medical Informatics Association : JAMIA2018

NLPReViz: an interactive tool for natural language processing on clinical text.

Gaurav Trivedi, Phuong Pham, Wendy W Chapman, Rebecca Hwa, Janyce Wiebe, Harry Hochheiser

Abstract read
In one paragraph

Article in Journal of the American Medical Informatics Association : JAMIA, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed, 1 pooled it
–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

11 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Article
  4. Translational NLP: A New Paradigm and General Principles for Natural Language Processing Research.Proceedings of the conference. Association for Computational Linguistics. North American Chapter. Meeting · 2021
    Article
  5. Article
  6. Review
  7. Article
  8. Extraction of Temporal Information from Clinical Narratives.Journal of healthcare informatics research · 2019
    Article
  9. Article
  10. NLPReViz: an interactive tool for natural language processing on clinical text.Journal of the American Medical Informatics Association : JAMIA · 2018
    Article
  11. Usability Evaluation of an Unstructured Clinical Document Query Tool for Researchers.AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science · 2018
    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

6 authors.

Gaurav TrivediIntelligent Systems Program, University of Pittsburgh, Pittsburgh, PA, USA.
Phuong PhamDepartment of Computer Science, University of Pittsburgh, Pittsburgh, PA, USA.
Wendy W ChapmanDepartment of Biomedical Informatics, University of Utah, Salt Lake City, UT, USA.
Rebecca HwaIntelligent Systems Program, University of Pittsburgh, Pittsburgh, PA, USA.
Janyce WiebeIntelligent Systems Program, University of Pittsburgh, Pittsburgh, PA, USA.
Harry HochheiserIntelligent Systems Program, University of Pittsburgh, Pittsburgh, PA, USA.

Funding

Interactive Search and Review of Clinical Records with Multi-Layered Semantic AnnotationsR01LM010964 · NLM · UNIVERSITY OF UTAH · PI CHAPMAN, WENDY W., HWA, REBECCA · 2011 to 2014
$2.3M
NLM NIH HHS R01 LM010964
6 · The paper itself

Abstract

The gap between domain experts and natural language processing expertise is a barrier to extracting understanding from clinical text. We describe a prototype tool for interactive review and revision of natural language processing models of binary concepts extracted from clinical notes. We evaluated our prototype in a user study involving 9 physicians, who used our tool to build and revise models for 2 colonoscopy quality variables. We report changes in performance relative to the quantity of feedback. Using initial training sets as small as 10 documents, expert review led to final F1scores for the "appendiceal-orifice" variable between 0.78 and 0.91 (with improvements ranging from 13.26% to 29.90%). F1for "biopsy" ranged between 0.88 and 0.94 (-1.52% to 11.74% improvements). The average System Usability Scale score was 70.56. Subjective feedback also suggests possible design improvements.

Indexed as

Electronic Health RecordsMachine LearningNatural Language ProcessingUser-Computer InterfaceAttitude of Health PersonnelColonoscopyHumansInformation Storage and RetrievalPhysiciansSoftwareelectronic health recordsmachine learningmedical informaticsnatural language processing (NLP)user-computer interface

Identifiers

PMID29016825
PMCPMC6381768

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.