engleski

Artificial intelligence based analysis of met-enkephalin induced immunomodulation in multiple sclerosis.

We present the analysis of met-enkephalin (LUPEX) induced effects on 52 different immunochemical parameters that define cellular and humoral immune response. In addition to the standard statistical analysis we used artificial intelligence data mining methods, i.e. nonlinear machine learning approach with C4.5 decision tree classifier and self organising artificial neural network. It is shown that artificial intelligence based methods of data analysis provide useful alternative to the standard statistical approach, enable the extraction of few relevant immunochemical parameters with their mutual relationships, and ensure accurate prediction of the response to drug treatment.

met-enkephalin; immunomodulation; multiple sclerosis; decision tree classifier; prognostic parameters; neural network

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