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Related Experiment Video

Updated: May 26, 2026

Pattern-based Search of Epigenomic Data Using GeNemo

Pattern-based Search of Epigenomic Data Using GeNemo

Published on: October 8, 2017

Search filter precision can be improved by NOTing out irrelevant content.

Nancy L Wilczynski¹, K Ann McKibbon, R Brian Haynes

¹Health Information Research Unit, McMaster University, Hamilton, Ontario, Canada.

AMIA ... Annual Symposium Proceedings. AMIA Symposium

|December 24, 2011

Summary

Improving search filter precision is possible by excluding irrelevant content. This method significantly enhances the number needed to read (NNR), making searches more efficient.

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Area of Science:

Information Science
Medical Informatics
Bibliometrics

Background:

Methodologic search filters in large databases like MEDLINE often lack precision.
Excluding irrelevant content, termed 'NOTing out,' is a proposed but untested strategy to enhance precision.

Purpose of the Study:

To evaluate if search filter precision improves by excluding off-target articles' text words and index terms.
Assessing the impact of 'NOTing out' on search filter performance across various databases and study purposes.

Main Methods:

Conducted an analytic survey.
Implemented 'NOTing out' of unique terms from off-target articles.
Evaluated search filter performance using sensitivity, specificity, and number needed to read (NNR) in the Clinical Hedges Database.

Main Results:

Excluding irrelevant content substantially improved NNR (over four-fold in some cases) for diagnosis, prognosis, and etiology categories across MEDLINE, EMBASE, CINAHL, and PsycINFO.
Improvements in NNR were observed across multiple databases, indicating the broad applicability of the 'NOTing out' strategy.

Conclusions:

Search filter precision can be effectively improved by excluding irrelevant content.
The 'NOTing out' strategy offers a practical approach to enhance the efficiency of information retrieval in medical databases.