AI DISEASE PREDICTION SYSTEM

Abstract

The AI Disease Prediction System is an intelligent healthcare platform developed using Artificial Intelligence, Machine Learning, and Deep Learning technologies to improve disease diagnosis accuracy and healthcare accessibility. Traditional healthcare systems often suffer from delayed diagnosis, shortage of specialists, high consultation costs, and human errors. The proposed system addresses these problems by providing automated disease prediction based on symptoms and medical image analysis. The system integrates ensemble Machine Learning algorithms such as Random Forest, Support Vector Machine (SVM), and Gradient Boosting for symptombased disease prediction. Additionally, a Convolutional Neural Network (CNN) based on ResNet-50 architecture is used for medical image classification including chest X-rays, skin lesion images, and retinal images. The platform also includes secure authentication, prediction history management, healthcare API integration, and an admin dashboard for monitoring and analytics. The proposed system achieved 89.1% accuracy in symptom-based disease prediction and 91.2% accuracy in image classification. The platform improves healthcare accessibility, reduces diagnosis time, minimizes manual effort, and enhances prediction reliability. The system demonstrates how Artificial Intelligence can transform modern healthcare systems through intelligent automation and predictive analytics.