The Chat project involves the implementation of dynamic and interactive data visualization features, specifically focusing on Bar Charts and Pie Charts. These charts are designed to display multiple measures with customizable display options, enhancing the user's ability to analyze and interpret data effectively.

This project is focused on developing an AI-driven retail platform using the MERN stack (MongoDB, Express.js, React.js, Node.js) to revolutionize the healthcare sector. The platform is designed to streamline product management, order tracking, and user engagement, ensuring a smooth experience for buyers, sellers, and administrators. With features like dynamic category management, personalized product recommendations, and affiliate marketing, it simplifies the journey from discovery to purchase while improving operational efficiency.

The objective of proposed application is to enhance the management of chronic care disease by facilitating comprehensive data collection, treatment adherence, and patient-provider communication. The application aims to address the current lack of real-world data and studies in urology. It enables healthcare providers to monitor patient-reported symptoms, track pain trends, and assess treatment efficac Doctors can access a dashboard displaying all  patients, prioritize cases based on symptom severity, and receive alerts for critical cases. Patients can easily log symptoms, monitor their  scores, and receive reminders for medications and lifestyle changes, ensuring better adherence to treatment plans. It enables secure messaging between patients and providers, allowing for timely updates, treatment adjustments, and symptom reports. Patients can access personalized educational materials, including multimedia resources and chatbot support, to manage their condition effectively. The platform aims to deliver personalized, data-driven care, improve patient outcomes, and contribute valuable real-world evidence to further research and understanding of the problem