Personalized medicine is a broad and rapidly advancing field of health care that is informed by each person's unique clinical, genetic, genomic, and environmental information. Health care that embraces personalized medicine is an integrated, coordinated, evidence based approach to individualizing patient care across the continuum. It is very important to make the right treatment decision but before that to obtain a good diagnosis. There are several clinical forms of disease whose symptoms vary depending on the age and etiology. In this study, we investigated and evaluated a model framework, for personalized diagnostic decisions, based on Case Based Fuzzy Cognitive Map (CBFCM, a cognitive process applying the main features of fuzzy logic and neural processors to situations involving imprecision and uncertain descriptions, in a similar way to intuitive human reasoning. We explored the use of this method for modelling clinical practice guidelines.