Evidence map›Paper›PMID 23676245›Full record

ReviewJournal of the American Medical Informatics Association : JAMIA

Temporal reasoning over clinical text: the state of the art.

Weiyi Sun, Anna Rumshisky, Ozlem Uzuner

Abstract readReview
In one paragraph

Review 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 19 papers.

0numbers the graph read from it
0cells of the map it votes in
19citing 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

19 citing papers in PubMed.

  1. Article
  2. Temporal Ensemble Logic for Integrative Representation of the Entirety of Clinical Trials.LIPIcs : Leibniz international proceedings in informatics · 2025
    Article
  3. [Significance of natural language processing and chat-based generative language models].Medizinische Klinik, Intensivmedizin und Notfallmedizin · 2024
    Review
  4. Article
  5. Article
  6. Article
  7. High-throughput phenotyping with temporal sequences.Journal of the American Medical Informatics Association : JAMIA · 2021
    Article
  8. Article
  9. Extraction of Temporal Information from Clinical Narratives.Journal of healthcare informatics research · 2019
    Article
  10. Review
  11. Review
  12. Automated methods for the summarization of electronic health records.Journal of the American Medical Informatics Association : JAMIA · 2015
    Review
  13. Normalization of relative and incomplete temporal expressions in clinical narratives.Journal of the American Medical Informatics Association : JAMIA · 2015
    Article
  14. Review
  15. Parameterizing time in electronic health record studies.Journal of the American Medical Informatics Association : JAMIA · 2015
    Article
  16. Annotating temporal information in clinical narratives.Journal of biomedical informatics · 2013
    Article
  17. Article
  18. Electronic health records-driven phenotyping: challenges, recent advances, and perspectives.Journal of the American Medical Informatics Association : JAMIA · 2013
    Article
  19. Patient-level temporal aggregation for text-based asthma status ascertainment.Journal of the American Medical Informatics Association : JAMIA
    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.

Weiyi SunDepartment of Informatics, University at Albany, SUNY, Albany, New York, USA.
Anna Rumshisky
Ozlem Uzuner

Funding

Informatics for Integrating Biology/ the Bedside (RMI)U54LM008748 · NLM · BRIGHAM AND WOMEN'S HOSPITAL · PI KOHANE, ISAAC S. · 2004 to 2013
$39.0M
Challenges in Natural Language Processing in Clinical TextR13LM011411 · NLM · STATE UNIVERSITY OF NEW YORK AT ALBANY · PI UZUNER, OZLEM · 2012 to 2016
$98k
NLM NIH HHS 1R13LM01141101NLM NIH HHS 2U54LM008748NLM NIH HHS R13 LM011411NLM NIH HHS U54 LM008748
6 · The paper itself

Abstract

objectivesTo provide an overview of the problem of temporal reasoning over clinical text and to summarize the state of the art in clinical natural language processing for this task. TARGET AUDIENCE: This overview targets medical informatics researchers who are unfamiliar with the problems and applications of temporal reasoning over clinical text. SCOPE: We review the major applications of text-based temporal reasoning, describe the challenges for software systems handling temporal information in clinical text, and give an overview of the state of the art. Finally, we present some perspectives on future research directions that emerged during the recent community-wide challenge on text-based temporal reasoning in the clinical domain.

Indexed as

Electronic Health RecordsNatural Language ProcessingArtificial IntelligenceHumansInformation Storage and RetrievalSoftwareTimeMedical language processingNatural language processingTemporal reasoning

Identifiers

PMID23676245
PMCPMC3756277

What OpenQuestion holds

Textmetadata
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.