CN Aarogya Mitra: A Multiple Disease Prediction System

CN Aarogya Mitra: A Multiple Disease Prediction System

Chinmay Shivratriwar1, Rahul Agarkar2, Yash Dharpure3, Soham Sarde4, Dr. K.P. Wagh5

1Department Of Information Technology, GCOE Amravati, Maharashtra 444604, India

2Department Of Information Technology, GCOE Amravati, Maharashtra 444604, India

3Department Of Information Technology, GCOE Amravati, Maharashtra 444604, India

4Department Of Information Technology, GCOE Amravati, Maharashtra 444604, India

5Asst. Prof. Department of Information Technology GCOE Amravati, Maharashtra 444604, India

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Abstract - The rise of chronic diseases has been steadily increasing in recent years, creating a significant impact on healthcare systems worldwide. Early detection and diagnosis of chronic diseases play a critical role in improving patient outcomes and reducing healthcare costs. Machine learning (ML) algorithms have shown promise in predicting the likelihood of chronic diseases by analyzing patient data.

In this research paper, we propose a Multiple Disease Prediction System (MDPS) that uses ML algorithms like Random Forest Algorithm to predict the likelihood of four chronic diseases: diabetes, kidney, liver and cancer. The proposed system utilizes a dataset of patient’s health record like blood parameters and different health related factors. The data was pre-processed, and features were extracted before being used to train four different ML models, each tailored to predict one of the four diseases. The models were then combined using an ensemble approach to make the final prediction

Key Words:  Multiple Disease Prediction System, Machine Learning, Random Forest Algorithm, Diabetes, Kidney, Liver, Cancer