Evidence map›Paper›PMID 35612107›Full record

ArticleStudies in health technology and informatics2022

An Ontology for Cardiothoracic Surgical Education and Clinical Data Analytics.

Maryam Panahiazar, Yorick Chern, Ramon Riojas, Omar S Latif, Usha Lokala, Dexter Hadley, Amit Sheth, Ramin E Beygui

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Studies in health technology and informatics, 2022. 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. 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

8 authors.

Maryam PanahiazarDepartment of Surgery, Division of Cardiothoracic Surgery, School of Medicine, University of California San Francisco, San Francisco, CA, USA.
Yorick ChernDepartment of Bioengineering, University of California Berkeley, Berkeley, CA, USA.
Ramon RiojasDepartment of Surgery, Division of Cardiothoracic Surgery, School of Medicine, University of California San Francisco, San Francisco, CA, USA.
Omar S LatifDepartment of Internal Medicine, Mayo Clinic, Rochester, MN, USA.
Usha LokalaDepartment of Computer Science and Engineering, Artificial Intelligence Institute, University of South Carolina, Columbia, SC, USA.
Dexter HadleyDepartment of Clinical Sciences, College of Medicine, University of Central Florida, Orlando, FL, USA.
Amit ShethDepartment of Computer Science and Engineering, Artificial Intelligence Institute, University of South Carolina, Columbia, SC, USA.
Ramin E BeyguiDepartment of Surgery, Division of Cardiothoracic Surgery, School of Medicine, University of California San Francisco, San Francisco, CA, USA.

Funding

Crowd-Assisted Deep Learning (CrADLe) Digital Curation to Translate Big Data into Precision MedicineU01LM012675 · NLM · UNIVERSITY OF CENTRAL FLORIDA · PI HADLEY, DEXTER D · 2017 to 2020
$2.1M
NLM NIH HHS U01 LM012675
6 · The paper itself

Abstract

The development of an ontology facilitates the organization of the variety of concepts used to describe different terms in different resources. The proposed ontology will facilitate the study of cardiothoracic surgical education and data analytics in electronic medical records (EMR) with the standard vocabulary.

Indexed as

Biological OntologiesData ScienceElectronic Health RecordsVocabularyCardiothoracic SurgeryCommon VocabularyEducationOntology

Identifiers

PMID35612107
PMCPMC10342192

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.