Cardiovascular Disease (CVD) Prediction Using Deep Learning Algorithm

Brain and Heart both organs keep our body working with co-ordination comparing to brain heart is very delicate and need more care for well-functioning. So heart is essential in every living body. Pumping of oxygenated blood and supplies it to all organs in proper flow makes our body well operated. So keeping our heart healthy and disease free is our priority. For this propose prediction of genesis of cardiovascular diseases will be very notable work in healthcare sector. Processing on raw data with useful tools and technique to make it significant for prediction of disease at early stage will be useful for healthcare center to cure disease at its born stage. Enormous disease related data of patients is stored every day in that can be pre-process and can be used to train any machine learning or deep learning model which will help to predict disease at early stage. In this study deep learning algorithms like RNN(Recurrent Neural Network) with its type LSTM(Long short Term Memory) is used to train and predict the cause of CVD so patient can start medication very soon. The proposed work, come up with comparative study of pervious used algorithm and proposed working algorithms with accurate prediction without time delay. The results of the diagnosis model are generated by using classification method, accuracy and severity of causing parameters. This review paper purpose is to develop the model to predict whether patient is having a cardiovascular disease or not and make patient more aware on CVD. The perfection is achieved by using categorization technique, RNN (Recurrent Neural Network) with LSTM to achieve accuracy in prediction.