Convergence based Optimization Algorithm Lung Disease Prediction by Convergence-Driven Optimization Algorithm

In the present world, the quick diagnosis of diseases is extremely important for modern healthcare systems. Every person needs quick and reliable medical assistance, and this is where technology is contributing significantly. In this regard, a new model called "Lung Disease Prediction Model" has been designed, which is a full-stack machine learning model for identifying and analyzing various lung diseases by applying deep learning techniques. This model is designed by using Python's Flask for the backend and React for the frontend. This system can collect information and images, perform image understanding by applying the Gemini API, and generate AI-based predictions by applying TensorFlow. In the context of security, email-based OTP authentication, JWT session management, and access control middleware are incorporated into the system. Besides this, a token bucket rate limiter is also being implemented to efficiently handle a large number of API calls. Communication between the patient and the doctor is also being facilitated by the addition of the Flask-SocketIO extension, thus improving the healthcare services. MongoDB is used as a database for increased flexibility in handling complex medical data. The purpose of developing this system is to create a unified platform for healthcare that combines data processing, real-time communication, and AI diagnosis in a single platform for better patient experiences and improved decision-making for doctors.