Heart Disease Prediction using Web Application and Random Forest Algorithm

• Published in: International Journal of Advanced Research in Science Communication and Technology pp. 48 - 52
• Main Authors: Mr. Yashas J, Anagha A V, Savantha V J, Sanjay K N, Rakesh N V
• Format: Journal Article
• Language: English
• Published: 16.07.2022
• ISSN: 2581-9429; 2581-9429
• DOI: 10.48175/IJARSCT-5780

Heart is the main organ of our body. In today’s world heart is one of the major fatal diseases and its prediction is quite difficult. This paper proposes a model to predict the heart disease using machine learning techniques. The proposed system involves data collection, data Preprocessing, data modeling and model deployment. The dataset collected has 14 columns and 421 rows corresponding to 14 medical attributes of 421 patients. This dataset is grouped for training and testing. Various machine learning algorithms were used to check the accuracy out of which the Random Forest Algorithm is best suited with an accuracy of 84%. The model is trained using random forest algorithm. Web app python code is used to load the model. The user can enter the details in the web application which is created using FLASK framework. The result is displays whether a person has heart disease or not based on the user input. If the person is predicted with heart disease then an alert message will be sent.