Fuzzy Logic System for Classifying Multiple Sclerosis Patients as High, Medium, or Low Responders to Interferon-Beta

Interferon-beta is one of the most widely prescribed disease-modifying therapies for multiple sclerosis patients. However, this treatment only partially effective, and a significant proportion patients do not respond to drug. This paper proposes an alternative fuzzy logic system, based on opinion neurology expert, classify relapsing–remitting as high, medium, or low responders interferon-beta. Also, pipeline prediction model trained with biomarkers associated interferon-beta responses proposed, predicting whether are potential candidates be treated drug, in order avoid ineffective therapies. The classification results showed that system presented 100% efficiency, compared unsupervised hierarchical clustering method (52%). So, performance was evaluated, 0.8 testing accuracy achieved. Hence, model, including data standardization, compression, learning algorithm, could useful tool getting reliable predictions about