Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
506014 | Computers in Biology and Medicine | 2006 | 15 Pages |
Abstract
Uncertainty is inherent in medical decision making and poses a challenge for intelligent technologies. This paper focuses on magnetic resonance spectra (MRS) for discrimination of brain tumour types and grades. Modelling of this type of high-dimensional data is commonly affected by uncertainty caused by the presence of outliers. Multivariate data clustering and visualization of MRS data is proposed using the GTM framework with basis functions comprising Student t-distributions in order to minimize the negative impact on the model from outliers. The effectiveness of this model on the MRS data is demonstrated empirically.
Related Topics
Physical Sciences and Engineering
Computer Science
Computer Science Applications
Authors
Alfredo Vellido, Paulo J.G. Lisboa,