• MOHAMMED JUNED
• Soham Shrikant Manjrekar
• Mohammed Danish Nisar Ahmed Khan
• MUZAFFAR MOHAMMAD SOAIB KHAN
• Danish Rashid Jamadar

Our point is to anticipate the various sorts of illness in a single stage by utilizing the inbuilt python module Streamlit. In this task we are utilizing Naïve Bayes algorithm, random forest, decision tree and svm classifier are utilized for prediction of a particular disease. The calculation which gives more accuracy is used to train the data set before implementation. To implement multiple disease analysis using machine learning algorithms, Streamlit and python pickling is utilized to save the model behavior. In this article we analyze Diabetes analysis, Heart disease and Parkinson’s disease by using some of the basic parameters such as Pulse Rate, Cholesterol, Blood Pressure, Heart Rate, etc., and also the risk factors associated with the disease can be found using prediction model with good accuracy and Precision. Further we can include other kinds of chronic diseases, skin diseases and many others. In this work, demonstrating that using only core health parameters many diseases can be predicted. The significance of this analysis is to analyze the maximum diseases to screen the patient's condition and caution the patients ahead of time to diminish mortality proportion. To implement multiple disease analysis used machine learning algorithms, Streamlit. We have considered three diseases for now that are Heart, Liver, and Diabetes and in the future, many more diseases can be added. The user has to enter various parameters of the disease and the system would display the output whether he/she has the disease or not. This project can help a lot of people as one can monitor the persons’ condition and take the necessary precautions thus increasing the life expectancy.

Diabetes, Heart, Liver, KNN, Random Forest, XG Boost.

"Multiple Disease Prediction Webapp", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.9, Issue 10, page no.e225-e234, October-2022, Available :http://www.jetir.org/papers/JETIR2210432.pdf

"Multiple Disease Prediction Webapp", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.9, Issue 10, page no. ppe225-e234, October-2022, Available at : http://www.jetir.org/papers/JETIR2210432.pdf