Multiple disease prediction using machine learning algorithms
Parth Dayal, Deepansh Sharma, Aman Agarwal, Himanshu Chaudhary, Ruchita Gautam, Praveen Kumar, Abhishek Sharma
Abstract
The prediction of the diseases was performed by taking different symptoms as input data from the user. In this paper, we have analyzed the presence of many diseases such as Heart diseases, CKD, Liver disease, and many more using basic body parameters such as blood sugar, heart rate, etc. We have applied the most used classification algorithms such as Logistic Regression, KNN, and Random Forest Classifier to anticipate the illness. Finally, the algorithm with the most accuracy is used to train the model. For the prediction of malaria and pneumonia, we have used Deep Learning (CNN) which extracts important information, and patterns from the images, match it against a large dataset it already has, and makes the prediction. All the models have good accuracy and have been combined into a single website for easy access.