Computational Intelligence Techniques Applied to Magnetic Resonance Spectroscopy Data of Human Brain Cancers

Computational intelligence techniques were applied to human brain cancer magnetic resonance spectral data. In particular, two approaches, Rough Sets and a Genetic Programming-based Neural Network were investigated and then confirmed via a systematic Individual Dichotomization algorithm. Good preliminary results were obtained with 100% training and 100% testing accuracy that differentiate normal versus malignant samples.Des techniques d'intelligence computationnelle ont \ue9t\ue9 appliqu\ue9es \ue0 l'analyse des donn\ue9es de spectres de r\ue9sonnance magn\ue9tique portant sur des tumeurs c\ue9r\ue9brales humaines. Plus particuli\ue8rement, nous avons examin\ue9 deux m\ue9thodes, les ensembles bruts et le r\ue9seau neuronal bas\ue9 sur la programmation g\ue9n\ue9tique, et avons confirm\ue9 leur utilit\ue9 au moyen d'un algorithme de dichotomisation individuelle syst\ue9matique. De bons r\ue9sultats pr\ue9liminaires permettant de distinguer les \ue9chantillons normaux des \ue9chantillons malins ont \ue9t\ue9 obtenus : exactitude de l'apprentissage de 100 % et exactitude du test de 100 %.NRC publication: Ye