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This study considers the construction of a multicriteria model to assist in the diagnosis of Alzheimerpsilas disease. Alzheimerpsilas disease is considered the most frequent of the dementias and it is responsible for about 50% of the cases. Due to this fact and the therapeutical limitations in the most advanced stage of the disease, diagnosis of Alzheimerpsilas disease is extremely important and it can provide better life conditions to patients and their families. The main focus of this work is to develop a multicriteria model for aiding in decision making for the diagnosis of Alzheimerpsilas disease, using Bayesian networks as a modeling tool. In this work, the modeling and evaluation processes have been conducted with the aid of a medical expert, bibliographic sources and battery of standardized assessments. The construction of cardinal value scales was implemented through Hiview and Macbeth.