Fuzzy Logic For Estimating Surgery Risks Based on ASA Classification

Abstract

The huge development of artificial intelligence in health care system dealing with uncertainties in the health decision‐making process. The fuzzy logic provides an effective income for dealing with uncertainties. This research practices fuzzy logic (FL) system to think like an expert clinician and exam the possibility of diagnosing the risk of performing surgical operations requiring general anesthesia. This done through the patient's main tests and analyses the levels of test results according to the American Society of General Anesthesia (ASA). Relying on fuzzy logic rules, the possibility of reducing huge input probabilities to four cases of output (no risk and three levels of risk). this were achieved according to the FL most successful Mamdani technique and using the Gaussian function as membership functions. The results showed an efficient result that aid physician committee in making important decisions related to the patient’s life.