Conference proceeding
Understanding the evolution of NSAID: A knowledge domain visualization approach to Evidence-Based Medicine
NINTH INTERNATIONAL CONFERENCE ON INFORMATION VISUALISATION, PROCEEDINGS, v 2005, pp 945-952
01 Jan 2005
Featured in Collection : UN Sustainable Development Goals @ Drexel
Abstract
Finding the most rigorous, updated, and well received clinical evidence is a crucial and challenging task in the practice of Evidence-Based Medicine (EBM). In this article, we describe a knowledge domain visualization-based quantitative approach that is designed to support the task of searching for high-quality clinical evidence in the medical literature. We illustrate the use of this new approach with the knowledge domain of Non-Steroidal Anti-Inflammatory Drugs (NSAIDs). A sample of the literature is visualized in a base map depicting structural and temporal properties of emerging themes and references made by such themes over time. In addition, the visualization highlights the rigorousness of a published clinical trial in terms of the type of study design retrieved dynamically from PubMed The contribution of this approach is that it offers users an integrated search environment so that the rigorousness, recentness, and consensus of clinical evidence can be assessed with the support of visual exploration facilities.
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Details
- Title
- Understanding the evolution of NSAID: A knowledge domain visualization approach to Evidence-Based Medicine
- Creators
- C M Chen - Drexel UniversityY N Chen - Drexel UniversityR C Maulitz - CHI Systems (United States)
- Contributors
- E Banissi (Editor)M Sarfraz (Editor)J C Roberts (Editor)B Loften (Editor)A Ursyn (Editor)R A Burkhard (Editor)A Lee (Editor)G Andrienko (Editor)
- Publication Details
- NINTH INTERNATIONAL CONFERENCE ON INFORMATION VISUALISATION, PROCEEDINGS, v 2005, pp 945-952
- Publisher
- IEEE
- Number of pages
- 8
- Resource Type
- Conference proceeding
- Language
- English
- Academic Unit
- Information Science; Family (Community and Preventive) Medicine
- Web of Science ID
- WOS:000230984100135
- Scopus ID
- 2-s2.0-33749077500
- Other Identifier
- 991019170381604721
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- Web of Science research areas
- Computer Science, Information Systems