Evidence map›Paper›PMID 37350894›Full record

ArticleAMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science2023

CRENO: An ontology to model concepts relating to culture, race, ethnicity, and nationality for health data.

Eloisa Nguyen, Muhammad Amith, Anne Nordberg, Lu Tang, Marcelline R Harris, Cui Tao

Abstract read
In one paragraph

Article in AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Hootation: A GUI and API library for ontology validation and verbalization.Proceedings. IEEE International Conference on Semantic Computing · 2026
    Article
  2. 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.

Eloisa NguyenSeattle Pacific University, Seattle, WA.
Muhammad AmithUniversity of North Texas, Denton, TX.
Anne NordbergUniversity of Texas, Arlington, TX.
Lu TangTexas A&M University, College Station, TX.
Marcelline R HarrisUniversity of Michigan, Ann Arbor, MI.
Cui TaoUniversity of Texas Health Science Center at Houston, Houston, TX.

Funding

Facilitate Observational Studies of Alzheimer's Disease and Alzheimer's Disease-Related Dementias Using Ontology and Natural Language ProcessingRF1AG072799 · NIA · YALE UNIVERSITY · PI LIU, HONGFANG, TAO, CUI · 2021 to 2021
$2.4M
NIA NIH HHS RF1 AG072799
6 · The paper itself

Abstract

Generating categories and classifications is a common function in life science research; however, categorizing the human population based on "race" remains controversial. There is an awareness and recognition of social-economic disparities with respect to health which are sometimes impacted by someone's ethnicity or race. This work describes an endeavor to develop a computable ontology model to represent a standardization of the concepts surrounding culture, race, ethnicity, and nationality - concepts misrepresented widely. We constructed an OWL ontology based on reliable resources with iterative human expert evaluations and aligned it to existing biomedical ontological models. The effort produced a preliminary ontology that expresses concepts related to classes of ethnic, racial, national, and cultural identities and showcases how health disparity data can be linked and expressed within our ontological framework. Future work will explore automated methods to expand the ontology and its utilization for clinical informatics.

Identifiers

PMID37350894
PMCPMC10283130

What OpenQuestion holds

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Registered trials

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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.