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. 2005:2005:121-5.

Searching for clinical evidence in CiteSpace

Chaomei Chen  1 , Yunan Chen
Affiliations

Searching for clinical evidence in CiteSpace

Chaomei Chen et al. AMIA Annu Symp Proc. 2005.

Abstract

A crucial step in the practice of evidence-based medicine is to locate the best available evidence regarding to clinical questions. In this article, we demonstrate that combining visualization techniques with traditional methods developed in evidence-based medicine could simplify the task. We describe a unifying framework for searching clinical evidence across multiple sources such as highly cited articles in the Web of Science and articles of particular types of study design in PubMed. We describe the implementation of a prototyping system to visualize the distribution of available evidence in a broader context of the underlying subject domain. We include examples of evidence found in the heart diseases and lung cancer literature. Practical implications on the design of visualization-based evidence searching tools are discussed.

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Figures

Figure 1
Figure 1
A unifying framework for finding evidence across complementary sources. Clinical evidence in subsequent visualizations is marked by publication type.
Figure 2
Figure 2
Overviews of the heart disease dataset: a) the network with no annotations; b) with burst terms; c) with evidence types; d) with only the landmark-landmark paths shown. Landmarks are nodes of high betweenness centrality, which is defined as the probability that an arbitrary shortest path passes a given node.
Figure 3
Figure 3
The timezone view of the heart disease example. The network contains 233 vertices and 599 edges. This is a top-cited subset of the entire data.
Figure 4
Figure 4
The cluster view of the lung cancer systematic review dataset, containing 467 items and 1,317 links.
Figure 5
Figure 5
The visualization of the lung cancer systematic review example. The top cluster is selected.
See this image and copyright information in PMC

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