Decision Support System to Risk Stratification in the Acute Coronary Syndrome Using Fuzzy Logic

Abstract

Acute coronary syndrome (ACS) is a set of symptoms and signs which define a range of conditions related with the unexpected reduced blood flow to the heart. In ACS, the heart muscles cannot function properly due to the decrease of blood flow. Myocardial infarction (MI) is a condition which comes under the umbrella of acute coronary syndrome. The aim of risk stratification (RS) in ACS is to recognize patients at high risk of ischemic events. Yet, no investigative study is available to identify the patients at high risk. Therefore, to facilitate this process, it would be ideal to have a reliable and trustworthy method by the help of which the doctors can make early and easy decisions for the patient and for detecting the related disease. This research used the features of GRACE Score to RS in the ACS and presented decision support system (DSS). The concept of probabilistic approach has been used as a tool to model the identified features for decision-making (DM). This technique can be further used for DM purposes to RS in the ACS in healthcare. Furthermore, the result of the proposed method has proved closer and more reliable DM of patient and then eventually can be used for advice of medicine and rest accordingly by the doctors.