R. Baumgartner

Complexity of Magnetic Resonance Spectrum Classification

Tin Kam Ho, Ray L. Somorjai, Uwe Himmelreich, 2006 .

The importance of appropriate (sparse) representation of data: Application to de-noising fMRI time courses

M. E. Alexander, R. Baumgartner, M. Alexander, 2001, NeuroImage.

Automated analysis of gene-microarray images

R. Baumgartner, Christopher N. Bowman, S. Booth, 2002, IEEE CCECE2002. Canadian Conference on Electrical and Computer Engineering. Conference Proceedings (Cat. No.02CH37373).

Consensus-based identification of spectral signatures for classification of high-dimensional biomedical spectra

Erinija Pranckeviciene, R. Baumgartner, R. Somorjai, 2004, ICPR 2004.

A Data-Driven, Flexible Machine Learning Strategy for the Classification of Biomedical Data

Murray E. Alexander, Erinija Pranckeviciene, Nicolino J. Pizzi, 2004, Artificial Intelligence Methods And Tools For Systems Biology.

Classification of human gliomas by infrared imaging spectroscopy and chemometric image processing

Gabriele Schackert, Claudia Beleites, Gerald Steiner, 2005 .

Variance reduction in estimating classification error using sparse datasets

Claudia Beleites, Ray L. Somorjai, Reiner Salzer, 2005 .

Correlator Beware: Correlation Has Limited Selectivity for fMRI Data Analysis

R. Baumgartner, R. Summers, R. Somorjai, 2000, NeuroImage.

Ranking fMRI Time Courses by Minimum Spanning Trees: Assessing Coactivation in fMRI

R. Baumgartner, R. Summers, R. Somorjai, 2001, NeuroImage.

Validating fuzzy clusters in fMRI data: A supervised approach

R. Baumgartner, R. Somorjai, M. Jarmasz, 2000, NeuroImage.