Development of an expert system algorithm for diagnosing cardiovascular disease using rough set theory implemented in MATLAB

• Main Author: Africa, Aaron Don M.
• Format: text
• Published: Animo Repository 2017
• Subjects: Cardiovascular system—Diseases—Diagnosis; Expert systems (Computer science); Biomedical engineering; Rough sets; Biomedical Devices and Instrumentation; Electrical and Computer Engineering
• Online Access: https://animorepository.dlsu.edu.ph/faculty_research/2514
• Institution: De La Salle University

Cardiovascular disease refers to conditions that involve narrow or blocked blood vessels. This disease when remained untreated may lead to a heart attack. When a person has a cardiovascular disease, The heart may not be able to pump enough blood to the body. When there is insufficient blood the brain or other organs may become damaged. Cardiovascular disease is challenging to diagnose because its symptoms may be mistaken for other diseases. Early detection, if a person has cardiovascular disease is a big advantage in combating the ailment. This is because diagnosing the disease early may reduce the complications it may bring. This research will develop an Expert System Algorithm for the diagnosis of cardiovascular disease. This research will guide the person diagnosing the disease to provide the appropriate recommendation. The Rough Set Theory will be used to reduce the rules so it can be easily diagnosed. This research will utilize the Statlog Heart Data Set of the UCI machine learning repository. Matrix Laboratory or MATLAB will be used to implement the system. © 2006-2017 Asian Research Publishing Network (ARPN).