Latest trends on heart disease prediction using machine learning and image fusion

Disease diagnosis is the most critical health-care function. If an illness is diagnosed before the normal or planned period it can save people's lives. Classification method of machine learning can be useful to help the medical branch by delivering reliable and instant disease diagnosis. Hence the convenient time for both physicians and patients because heart disease is one of the world's most ultra-hazardous and dangerous diseases today, due to the difficulty to diagnose the disease. Within this paper we include a review of the classification methods for machine learning and image fusion that have been demonstrated to help healthcare professionals identify heart disease. We begin with the machine learning brief and summarize descriptions of the mainly used classification techniques for diagnosing diseases of heart. Then, we review and demonstrate some work on the use of classification techniques for machine learning and image fusion in this area. It also provides an overview of the working algorithm, and provides a description of the current work. (C) 2020 Elsevier Ltd. All rights reserved.