Forecasting and Diagnosing Cardiovascular Disease Based on Inverse Fuzzy Models

Abstract

Advance formalization of a generalized fuzzy-logic mathematical model for forecasting and diagnosing cardiovascular complications is described. The model improves time of decision-making of anesthetist regarding the causes of complications and optimizes the perioperative period by prenosological prevention of occurring precursors of complications, reducing their total number and severity of clinical manifestations.