Disease Prediction using Real-Life Data and Machine Learning Algorithms

This paper presents a project on disease prediction using machine learning techniques. The goal of the project is to develop a web application that can forecast major diseases such as Parkinson’s disease, diabetes, heart disease, and brain tumors. The project utilizes a hybrid model that combines Convolutional Neural Network (CNN) and Support Vector Machine (SVM) models for disease prediction. The web application allows users to input relevant medical information and receive accurate estimates of their likelihood of developing these diseases. The project demonstrates the potential of machine learning in the early detection and prevention of dangerous diseases, although it currently has limitations in predicting only four major diseases.