An Analysis of Cardiovascular Disease Classification using Extreme Learning Machine

Abstract

Medical diagnosis is considered an art regardless of all standardization efforts that is greatly owing to the fact that medical diagnosis are necessary for an expertise in coping with uncertainty simply not found in today's computing machinery. One of mainly used technique in medicine is Data Mining, a relative new and multidisciplinary field which are capable to extract valuable information from large sets of data. Despite this fact, in cardiology related studies it was rarely used. Heart disease is the leading cause of death in the world over the past 10 years. Diabetes is a chronic disease which occurs due to when the pancreas does not produce enough insulin or when the body cannot effectively use the insulin it produces. This work uses Extreme learning Machines for the classification purpose. ELM are a modern classification technique in the field of machine learning and have been successfully using in different fields of application. The experimental results obtained which shows that Extreme learning machine can be successfully used for diagnosing cardiovascular disease.