A model-based approach to visualizing classification decisions for patient diagnosis


Conference Paper

Automated classification systems are often used for patient diagnosis. In many cases, the rationale behind a decision is as important as the decision itself. Here we detail a method of visualizing the criteria used by a decision tree classifier to provide support, for clinicians interested in diagnosing corneal disease. We leverage properties of our data transformation to create surfaces highlighting the details deemed important in classification. Preliminary results indicate that the features illustrated by our visualization method are indeed the criteria that often lead to a correct diagnosis and that our system also seems to find favor with practicing clinicians. © Springer-Verlag Berlin Heidelberg 2005.

Duke Authors

Cited Authors

  • Marsolo, K; Parthasarathy, S; Twa, M; Bullimore, M

Published Date

  • December 1, 2005

Published In

Volume / Issue

  • 3581 LNAI /

Start / End Page

  • 473 - 483

Electronic International Standard Serial Number (EISSN)

  • 1611-3349

International Standard Serial Number (ISSN)

  • 0302-9743

International Standard Book Number 10 (ISBN-10)

  • 3540278311

International Standard Book Number 13 (ISBN-13)

  • 9783540278313

Citation Source

  • Scopus