Evidence map›Paper›PMID 19683066›Full record

ReviewJournal of biomedical informatics2009

What can natural language processing do for clinical decision support?

Dina Demner-Fushman, Wendy W Chapman, Clement J McDonald

Abstract readReview
In one paragraph

Review in Journal of biomedical informatics, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 229 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
229citing papers in PubMed, 3 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

229 citing papers in PubMed, 3 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Pooled it
  4. Trial
  5. Review
  6. Article
  7. Article
  8. Artificial intelligence for personalized multiple micronutrient supplementation in maternal health.International journal of gynaecology and obstetrics: the official organ of the International Federation of Gynaecology and Obstetrics · 2026
    Review
  9. Article
  10. Article
  11. Between the scalpel and algorithms: how AI is redesigning Surgery.Revista do Colegio Brasileiro de Cirurgioes · 2026
    Article
  12. Efficient extraction of medication information from clinical notes: an evaluation in 2 languages.Journal of the American Medical Informatics Association : JAMIA · 2025
    Article
  13. Review
  14. Article
  15. Article
  16. Article
  17. Article
  18. Article
  19. Article
  20. Article

169 more citing papers are in PubMed but not listed here.

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.

Dina Demner-FushmanU.S. National Library of Medicine, National Institutes of Health, Bethesda, MD 20894, USA. ddemner@mail.nih.gov
Wendy W Chapman
Clement J McDonald

Funding

National Biomedical Information ServicesZIHLM200888 · NLM · NATIONAL LIBRARY OF MEDICINE · PI PALTOO, DINA · 2009 to 2025
$5200.7M
NLM's Personal Health Record and Consumer Service R&DZIALM008925 · NLM · NATIONAL LIBRARY OF MEDICINE · PI MCDONALD, CLEMENT · 2009 to 2020
$11.8M
Using large Clinical Data bases to assess the association between patient factors, medication usage and patient outcomesZIALM008927 · NLM · NATIONAL LIBRARY OF MEDICINE · PI MCDONALD, CLEMENT · 2009 to 2015
$1.5M
Intramural NIH HHS Z99 LM999999
6 · The paper itself

Abstract

Computerized clinical decision support (CDS) aims to aid decision making of health care providers and the public by providing easily accessible health-related information at the point and time it is needed. natural language processing (NLP) is instrumental in using free-text information to drive CDS, representing clinical knowledge and CDS interventions in standardized formats, and leveraging clinical narrative. The early innovative NLP research of clinical narrative was followed by a period of stable research conducted at the major clinical centers and a shift of mainstream interest to biomedical NLP. This review primarily focuses on the recently renewed interest in development of fundamental NLP methods and advances in the NLP systems for CDS. The current solutions to challenges posed by distinct sublanguages, intended user groups, and support goals are discussed.

Indexed as

Decision Support Systems, ClinicalNatural Language ProcessingDecision Making, Computer-AssistedHumansModels, Theoretical

Identifiers

PMID19683066
PMCPMC2757540

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.