Classification and Analysis of Disease over Symptoms using AI

Abstract: This paper presents a smart healthcare system that integrates machine learning-based disease prediction with an online appointment booking platform. The system aims to address the problem of delayed diagnosis and limited access to medical consultation by combining predictive analytics with real-time healthcare services. Machine learning algorithms such as Support Vector Machine (SVM) and Logistic Regression are used to predict diseases like diabetes, heart disease, and Parkinson’s based on user input data.

In addition to prediction, the system provides a web-based interface where patients can easily browse doctors and book appointments. The platform includes role-based dashboards for patients, doctors, and administrators, enabling efficient management of appointments, patient records, and doctor availability. The integration of prediction and booking ensures that users can take immediate action after receiving health insights.

The proposed system improves early detection, reduces manual effort, and enhances accessibility to healthcare services. It also provides a scalable and user-friendly solution that can be deployed in real-world healthcare environments. This approach demonstrates how the combination of machine learning and full-stack development can significantly improve healthcare delivery and patient outcomes.

The system is designed to be user-friendly, scalable, and efficient for real-world healthcare applications. It ensures secure data handling and smooth integration between prediction and booking modules. The approach reduces the gap between diagnosis and consultation, improves patient engagement, and helps healthcare providers manage patient flow effectively.

Keyword: Artificial Intelligence, Machine Learning, Disease Prediction, Healthcare Analytics, Diabetes Prediction, Heart Disease Detection, Parkinson’s Prediction, Predictive Modeling, Clinical Decision Support System, Streamlit Web Application, Medical Data Analysis, Early Diagnosis, Health Monitoring System, AI in Healthcare, Appointment Booking System Integration