Application of fuzzy logic for Alzheimer´s disease diagnosis

Fuzzy Inference System (FIS) is developed using subtractive clustering algorithm, and applied to classification between MRI images of patients having Mild Cognitive Impairment (MCI) or Alzheimer´s Disease (AD) and Normal Controls (NC). Features used as FIS inputs are mean values and standard deviations in intensities from most descriptive brain regions. k-fold cross-validation was used to estimate FIS performance, resulting in accuracy, sensitivity, specificity and positive predictive value (ppv) characteristics of FIS classification between different groups. ppv was equal to 0.8778±0.0088 (AD vs. NC), 0.7289±0.0243 (NC vs. MCI), and 0.8531±0.0069 (MCI vs. AD).