Evidence map›Paper›PMID 21347099›Full record

ArticleAMIA ... Annual Symposium proceedings. AMIA Symposium2010

Integrating heterogeneous knowledge sources to acquire executable drug-related knowledge.

Xiaoyan Wang, Herbert S Chase, Jianhua Li, George Hripcsak, Carol Friedman

Abstract read
In one paragraph

Article in AMIA ... Annual Symposium proceedings. AMIA Symposium, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing 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

10 citing papers in PubMed.

  1. Evaluating NLP Approaches to Extract Drug Indications.AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science · 2026
    Article
  2. Hierarchical Concept Relations Improve Detection of Off-Label Drug Use in Electronic Health Records Data.AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science · 2023
    Article
  3. Developing a Data-driven Medication Indication Knowledge Base using a Large Scale Medical Claims Database.AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science · 2019
    Article
  4. Article
  5. A pipeline to extract drug-adverse event pairs from multiple data sources.BMC medical informatics and decision making · 2014
    Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. 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

5 authors.

Xiaoyan WangDepartment of Biomedical Informatics, Columbia University, New York, NY.
Herbert S Chase
Jianhua Li
George Hripcsak
Carol Friedman

Funding

Training in Biomedical Informatics at Columbia UniversityT15LM007079 · NLM · COLUMBIA UNIV NEW YORK MORNINGSIDE · PI NOEMIE ELHADAD, GEORGE M HRIPCSAK · 1992 to 2026
$28.9M
DISCOVERING AND APPLYING KNOWLEDGE IN CLINICAL DATABASESR01LM006910 · NLM · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI HRIPCSAK, GEORGE M · 2000 to 2023
$10.6M
Pharmacovigilence using Natural Language Processing, Statistics, and the EHRR01LM010016 · NLM · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI FRIEDMAN, CAROL · 2009 to 2016
$3.4M
A Biomedical Natural Language Processing ResourceR01LM008635 · NLM · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI FRIEDMAN, CAROL · 2005 to 2008
$2.1M
NLM NIH HHS R01 LM006910NLM NIH HHS R01 LM008635NLM NIH HHS R01 LM010016NLM NIH HHS T15 LM007079
6 · The paper itself

Abstract

Knowledge of medical entities, such as drug-related information is critical for many automated biomedical applications, such as decision support and pharmacovigilance. In this work, heterogeneous information sources were integrated automatically to obtain drug-related knowledge. We focus on one type of knowledge, drug-treats-condition, in the study and propose a framework for integrating disparate knowledge sources. Evaluation based on a random sample of drug-condition pairs indicated an overall coverage of 96%, recall of 98% and a precision of 87%. In conclusion, the preliminary study demonstrated that the knowledge generated from this study was comparable to the manually curated gold standard and that this method of automatically integrating knowledge sources is effective. The automated method should also be applicable to integrate other clinical knowledge, such as drug-related knowledge with omics information.

Indexed as

PharmacovigilanceHumans

Identifiers

PMID21347099
PMCPMC3041361

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.