Add to ORKGA Feature Selection process with Single-Layer Perceptrons is shown to provide optimum discrimination of an international, multi-centre 1H-MRS database of brain tumors at reasonable computational cost. Results are both intuitively interpretable and very accurate. The method remains simple enough as to allow its easy integration in existing medical decision support systems
Contains fulltext : 92148.pdf (publisher's version ) (Closed access)11 p
[EN] This study examines the effect of feature extraction methods prior to automated pattern recogni...
Abstract. Machine learning is a powerful paradigm within which to analyze 1H-MRS spectral data for t...
A Feature Selection (FS) process with a simple Machine Learning method, namely the Single-Layer Perc...
The combination of an Artificial Neural Network classifier, a feature selection process, and a novel...
In cancer diagnosis, classification of the different tumor types is of great importance. An accurate...
In cancer diagnosis, classification of the different tumor types is of great importance. An accurate...
Accuracy is the most important quality marker in medical image segmentation. However, when the task ...
International audienceA computer-based decision support system to assist radiologists in diagnosing ...
A computer-based decision support system to assist radiologists in diagnosing and grading brain tumo...
Peer-reviewedWe are developing a decision support tool, based on a large \training" database of spec...
This study examines the effect of feature extraction methods prior to automated pattern recognition ...
Machine learning is a powerful paradigm within which to analyze 1HMRS spectral data for the classifi...
The purpose of this thesis is to investigate whether an automated medical decision support system th...
Contains fulltext : 52861.pdf (publisher's version ) (Closed access)OBJECTIVE: Thi...
Contains fulltext : 92148.pdf (publisher's version ) (Closed access)11 p
[EN] This study examines the effect of feature extraction methods prior to automated pattern recogni...
Abstract. Machine learning is a powerful paradigm within which to analyze 1H-MRS spectral data for t...
A Feature Selection (FS) process with a simple Machine Learning method, namely the Single-Layer Perc...
The combination of an Artificial Neural Network classifier, a feature selection process, and a novel...
In cancer diagnosis, classification of the different tumor types is of great importance. An accurate...
In cancer diagnosis, classification of the different tumor types is of great importance. An accurate...
Accuracy is the most important quality marker in medical image segmentation. However, when the task ...
International audienceA computer-based decision support system to assist radiologists in diagnosing ...
A computer-based decision support system to assist radiologists in diagnosing and grading brain tumo...
Peer-reviewedWe are developing a decision support tool, based on a large \training" database of spec...
This study examines the effect of feature extraction methods prior to automated pattern recognition ...
Machine learning is a powerful paradigm within which to analyze 1HMRS spectral data for the classifi...
The purpose of this thesis is to investigate whether an automated medical decision support system th...
Contains fulltext : 52861.pdf (publisher's version ) (Closed access)OBJECTIVE: Thi...
Contains fulltext : 92148.pdf (publisher's version ) (Closed access)11 p
[EN] This study examines the effect of feature extraction methods prior to automated pattern recogni...
Abstract. Machine learning is a powerful paradigm within which to analyze 1H-MRS spectral data for t...