Evidence map›Paper›PMID 23920664›Full record

ArticleStudies in health technology and informatics2013

Predicate argument structure frames for modeling information in operative notes.

Yan Wang, Serguei Pakhomov, Genevieve B Melton

Abstract read
In one paragraph

Article in Studies in health technology and informatics, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. The robotic-surgery propositional bank.Language resources and evaluation · 2024
    Article
  2. Semantic Role Labeling of Clinical Text: Comparing Syntactic Parsers and Features.AMIA ... Annual Symposium proceedings. AMIA Symposium · 2016
    Article
  3. Domain adaptation for semantic role labeling of clinical text.Journal of the American Medical Informatics Association : JAMIA · 2015
    Article
  4. 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.

Yan WangInstitute for Health Informatics, University of Minnesota, Minneapolis, MN, USA.
Serguei Pakhomov
Genevieve B Melton

Funding

Sematic Relatedness for Active Medication Safety and Outcomes SurveillanceR01LM009623 · NLM · UNIVERSITY OF MINNESOTA · PI PAKHOMOV, SERGUEI VS · 2008 to 2010
$949k
NLM NIH HHS R01 LM009623NLM NIH HHS R01 LM009623-01
6 · The paper itself

Abstract

The rich information about surgical procedures contained in operative notes is a valuable data source for improving the clinical evidence base and clinical research. In this study, we propose a set of Predicate Argument Structure (PAS) frames for surgical action verbs to assist in the creation of an information extraction (IE) system to automatically extract details about the techniques, equipment, and operative steps from operative notes. We created PropBank style PAS frames for the 30 top surgical action verbs based on examination of randomly selected sample sentences from 3,000 Laparoscopic Cholecystectomy notes. To assess completeness of the PAS frames to represent usage of same action verbs, we evaluated the PAS frames created on sample sentences from operative notes of 6 other gastrointestinal surgical procedures. Our results showed that the PAS frames created with one type of surgery can successfully denote the usage of the same verbs in operative notes of broader surgical categories.

Indexed as

Models, TheoreticalNatural Language ProcessingVocabulary, ControlledArtificial IntelligenceData MiningDocumentationElectronic Health RecordsInformation Storage and RetrievalPattern Recognition, AutomatedSemanticsSurgical Procedures, Operative

Identifiers

PMID23920664
PMCPMC4662251

What OpenQuestion holds

Textmetadata
LicenceTDM
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.