Visualisation of Multidimensional Data for Medical Decision Support

Authors:
Anne Rosemary Tate;Joshua Underwood;Christophe Ladroue;Rosemary Luckin;John R. Griffiths
Affiliations:
-;-;-;-;-
Venue:
AIME '01 Proceedings of the 8th Conference on AI in Medicine in Europe: Artificial Intelligence Medicine
Year:
2001

Citing 2
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Principles of multivariate analysis: a user's perspective

Principles of multivariate analysis: a user's perspective
Snap-together visualization: can users construct and operate coordinated visualizations?

International Journal of Human-Computer Studies - Empirical evaluation of information visualizations

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Abstract

Medical decision support tools are not widely used by clinicians, perhaps because most do not explain the decisions. We describe an approach for case-based systems using automated pattern recognition techniques. Multivariate methods estimate the degree of similarity between a new case and those in the database, and graphical displays allow users to combine this information with their own expertise. The approach is demonstrated by an example, the Spectra Visualizer, which allows radiologists to interpret magnetic resonance spectra. The variables in the overview are derived directly from the signals obtained from the scanner. Spectra with similar classification profiles can be linked to clinical history, images and expert commentary.