Orvostechnikai és biotechnikai műszaki tudományok és technológia
In this paper, we present a multilevel fuzzy inference model for predicting the risk
of type 2 diabetes. We have designed a system for predicting this risk by taking into
account various factors such as physical, behavioral, and environmental parameters
related to the investigated patient and thus facilitate experts to diagnose the risk
of diabetes. The important risk parameters of type 2 diabetes are identified based
on the literature and the recommendations of experts. The parameters are scaled and
fuzzified on their own universe and, based on the experts’ recommendation, fuzzy inference
subsystems are created with 3–4 related risk parameters to calculate the risk level.
These sub-systems are then arranged into Mamdani-type inference systems so that the
system calculates an aggregated risk level. The overview of the large number of diverse
types of risk factors, which may be difficult for specialists and doctors, is facilitated
by the proposed system.
