A Fuzzy Inference System to Support Medical Diagnosis in Real Time

This paper presents a Fuzzy Inference System created to support medical diagnoses in real time. It minimizes health costs and maximizes health resources based on real data selected by medical groups in the market. This renders support in posting qualified interview decisions through new Customer Risk Mapping. The main objective is to create a foundation of health resources for hospitals administrators based on medical decision procedures thus increasing the capacity for hospitals to absorb new processing techniques and consequently, ensuring higher quality services for their patients. The aim of this system is to delineate patient-risk-factor during a qualifying interview. The automation of this process becomes a benefit by establishing a real-time responses which needs not be applied by a doctor (can be executed by nurses), and, in return, characterizes an opportunity cost for the hospital.