Evidence map›Paper›PMID 10833166›Full record

ArticleJournal of the American Medical Informatics Association : JAMIA

From data to knowledge through concept-oriented terminologies: experience with the Medical Entities Dictionary.

J J Cimino

Abstract read
In one paragraph

Article in Journal of the American Medical Informatics Association : JAMIA. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 42 papers.

0numbers the graph read from it
0cells of the map it votes in
42citing 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

42 citing papers in PubMed.

  1. Trial
  2. Leveraging Knowledge Representation to Maintain Immunization Clinical Decision Support.AMIA ... Annual Symposium proceedings. AMIA Symposium · 2018
    Article
  3. Federated Tensor Factorization for Computational Phenotyping.KDD : proceedings. International Conference on Knowledge Discovery & Data Mining · 2017
    Article
  4. Review
  5. Article
  6. Article
  7. Article
  8. Article
  9. Defining a comprehensive verotype using electronic health records for personalized medicine.Journal of the American Medical Informatics Association : JAMIA · 2013
    Article
  10. Evaluation considerations for EHR-based phenotyping algorithms: A case study for drug-induced liver injury.AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science · 2013
    Article
  11. Practical choices for infobutton customization: experience from four sites.AMIA ... Annual Symposium proceedings. AMIA Symposium · 2013
    Article
  12. Using the LOINC Semantic Structure to Integrate Community-based Survey Items into a Concept-based Enterprise Data Dictionary to Support Comparative Effectiveness Research.NI 2012 : 11th International Congress on Nursing Informatics, June 23-27, 2012, Montreal, Canada. International Congress in Nursing Informatics (11th : 2012 : Montreal, Quebec) · 2012
    Article
  13. Chapter 1: Biomedical knowledge integration.PLoS computational biology · 2012
    Article
  14. Article
  15. Article
  16. Article
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  20. Review
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

1 author.

J J CiminoColumbia University, College of Physicians and Surgeons, New York, New York, USA. ciminoj@flux.cpmc.columbia.edu

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Knowledge representation involves enumeration of conceptual symbols and arrangement of these symbols into some meaningful structure. Medical knowledge representation has traditionally focused more on the structure than the symbols. Several significant efforts are under way, at local, national, and international levels, to address the representation of the symbols though the creation of high-quality terminologies that are themselves knowledge based. This paper reviews these efforts, including the Medical Entities Dictionary (MED) in use at Columbia University and the New York Presbyterian Hospital. A decade's experience with the MED is summarized to serve as a proof-of-concept that knowledge-based terminologies can support the use of coded patient data for a variety of knowledge-based activities, including the improved understanding of patient data, the access of information sources relevant to specific patient care problems, the application of expert systems directly to the care of patients, and the discovery of new medical knowledge. The terminological knowledge in the MED has also been used successfully to support clinical application development and maintenance, including that of the MED itself. On the basis of this experience, current efforts to create standard knowledge-based terminologies appear to be justified.

Indexed as

Artificial IntelligenceDictionaries, Medical as TopicTerminology as TopicDecision Support Systems, ClinicalInformation Storage and RetrievalMedical Records Systems, ComputerizedUnified Medical Language SystemVocabulary, Controlled

Identifiers

PMID10833166
PMCPMC61432

What OpenQuestion holds

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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.