Heart Disease Prediction System
Keywords:Machine Learning, Flask, Artificial Neural Network, Random Forest, Data analysis
It might have happened many times that you need doctors to facilitate instantly, however, they’re not always available, or sometimes it’s all about the formalities before checkin thanks for some reason. This project is based on the Web Application for Online Consultancy for people all around the world. This WebApp allows us to consult ourselves while sitting at our home. Here we propose a system that enables users to urge instant direction on their health problems through an associate intelligent health care system. Nowadays, health diseases are increasing day by day due to lifestyle, hereditary. Each individual has different values for Blood pressure, Cholesterol, and Pulse rate. This project comprises different classification techniques used for predicting the risk level of each person based on Age, Gender, Blood pressure, Cholesterol, Pulse rate, etc. The system analyzes the symptoms provided by the user as input and predicts the occurrence of the disease as an output. Disease Prediction is done by implementing six algorithm techniques such as KNN, Decision Tree, Logistic Regression and Random Forest, SVM, Artificial Neural Network with 1 hidden layer. This project also provides an intuition on EDA. Further, the web platform is composed of predicting the health risk of the user, providing the users with necessary suggestions depending on their health conditions.
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scikit-learn, keras, pandas and matplotlib
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