Health Platform Project

In this project, I developed a comprehensive web application that analyzes and visualizes various health-related data points using advanced machine-learning techniques. The application integrates multiple functionalities, including a user authentication system, data visualization, a chatbot for interacting with health records, and a specialized module for predicting health outcomes based on X-ray images.

The project's core involved creating a Flask-based web application that allows users to upload and analyze their health data. This data includes lab results, smoking rates, air quality, and population metrics, all visualized through dynamically generated plots. The application also incorporates an AI-powered chatbot that interacts with the user’s health data, providing summaries and insights based on the information uploaded.

One of the most challenging and rewarding aspects of the project was the implementation of a convolutional neural network (CNN) to analyze X-ray images and predict health outcomes, such as the presence of pneumonia. I trained the CNN model using a dataset of chest X-ray images and integrated the model into the application, allowing users to upload X-ray images and receive predictions directly through the web interface.

To enhance user experience, I ensured that the application was not only functional but also user-friendly. This included creating a clean and intuitive dashboard with easy navigation to various sections of the site, including the X-ray prediction module. The application also features a robust backend that handles user data securely, processes image files, and manages interactions with the trained machine learning model.