Author : Miss. Srushti N. Raut and Prof. Vikas M. Patil

Heart disease is one of the leading cause of death globally because of change in lifestyle of human being. Around 90% of cardiovascular disease can be prevented. Expectation of cardiovascular infection is a basic test in the region of clinical information examination. Health care fields have a vast amount of data, for processing those data certain technologies are used. Machine learning strategies are one of the effective for prediction. Different investigations give just a look into anticipating heart ailment with ML systems. Predict the cause and disease is one of the major challenges now a days. In this paper, we propose a novel strategy that targets finding huge includes by applying AI systems bringing about improving the exactness in the forecast of cardiovascular disease. In Artificial neural network model consist image processing, Image Filtering, Feature Extraction, Segmentation, Edge Detection and Feature Recognition steps. We use Python and Open-CV to make our detector and recognizer. ANN is one of the ML procedures which can be utilized to accomplish productive conclusion results and SVM classifier for getting fusion of results. We are using hybrid machine learning techniques of ANN and SVM for prediction. The proposed framework with ANN and fiveoverlap cross approval are gives 83% grouping exactness with mainly 4 different type of heart disease.

Keywords: Artificial         Neural   Network,              Heart     Disease,Machine Learning