An optimal algorithm for approximate nearest neighbor searching fixed dimensions
Journal of the ACM (JACM)
Exception safety: concepts and techniques
Advances in exception handling techniques
In Defense of One-Vs-All Classification
The Journal of Machine Learning Research
No Unbiased Estimator of the Variance of K-Fold Cross-Validation
The Journal of Machine Learning Research
An introduction to ROC analysis
Pattern Recognition Letters - Special issue: ROC analysis in pattern recognition
Computer Methods and Programs in Biomedicine
Statistical Comparisons of Classifiers over Multiple Data Sets
The Journal of Machine Learning Research
A note on Platt's probabilistic outputs for support vector machines
Machine Learning
HealthAgents: distributed multi-agent brain tumor diagnosis and prognosis
Applied Intelligence
Proceedings of the 29th DAGM conference on Pattern recognition
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We present an object-oriented library for the systematic training, testing and benchmarking of classification algorithms for computer-assisted diagnosis tasks, with a focus on tumor probability estimation from magnetic resonance spectroscopy imaging (MRSI) measurements. In connection with a graphical user interface for data annotation, it allows clinical end users to flexibly adapt these classifiers towards changed classification tasks, to benchmark various classifiers and preprocessing steps and to perform quality control of the results. This poses an advantage over previous classification software solutions, which required expert knowledge in pattern recognition techniques in order to adapt them to changes in the data acquisition protocols. This software will constitute a major part of the MRSI analysis functionality of RONDO, an integrated software platform for cancer diagnosis and therapy planning which is under current development.