Towards Designing A Hierarchical Fuzzy System for Early Diagnosis of Heart Disease

• Published in: Journal of Computing Research and Innovation Vol. 4; no. 2; pp. 31 - 41
• Main Authors: Tajul Rosli Razak, Iman Hazwam Abd Halim, Muhammad Nabil Fikri Jamaluddin, Mohammad Hafiz Ismail, Shukor Sanim Mohd Fauzi, Ray Adderley JM Gining
• Format: Journal Article
• Language: English
• Published: Faculty of Computer and Mathematical Sciences, Universiti Teknologi MARA Perlis 01-11-2019
• ISSN: 2600-8793

Heart disease may represent a range of conditions that affect our heart. Disease under heart diseases umbrella include coronary heart disease, heart attack, congestive heart failure, and congenital heart disease, is the leading cause of death. Moreover, heart disease not only attacks the elderly. In the present day, lots of younger people might be getting affected by the number of heart diseases. In order to decrease the mortality rate caused by heart disease, it is necessary for the disease, to be diagnosed at an early stage. In this paper, we have proposed the use of hierarchical fuzzy systems (HFSs) for early diagnosis of heart disease. However, to design the HFSs is challenging, especially for the complex system. Therefore, in this paper, we focus on designing a hierarchical fuzzy system to handle the complex medical application. The designed HFS consists of six key main steps implemented on heart disease. The input variables of heart disease includes shortness of breath, discomfort, pressure, heaviness, or pain in the chest, arm, or below the breastbone, fatigue, nausea, difficulties in climbing stairs, swelling in ankles, difficulty to sleep at night, irregular heartbeats, fullness, sweating, take frequent break during the day, dizzy and depressed. Additionally, the output of heart disease is to classify whether the patient is healthy or suspecting with heart disease. The study contributes to providing insight into a way of designing the HFSs, particularly for the complex medical application.