Our HealthAssist web application represents a breakthrough in the field of digital healthcare solutions. Leveraging cutting-edge artificial intelligence and machine learning technologies, our platform empowers users to take charge of their health and well-being with unprecedented ease and accuracy. With features like Disease prediction, users can quickly assess their health status by inputting their symptoms and even fine-tune the AI models with their own data for highly personalized results. Medication safety is ensured through an innovative Pill Quality Checker that swiftly analyzes pill images, providing instant feedback on their condition. For timely medical guidance and information, our responsive health chatbot is available round-the-clock, engaging users in meaningful conversations and offering expert advice.
In addition to these core features, our application excels in Medical Image Processing, accurately detecting pneumonia in X-ray images and providing probability scores to aid healthcare professionals in diagnosis. For users seeking health-related products, our platform offers Personalized recommendations from popular online marketplaces, facilitating informed choices. With a user-friendly interface developed using Streamlit, a high-performance backend powered by FastAPI, and the optimization of machine learning models using Intel OneAPI Libraries, we aim to make healthcare smarter, more accessible, and safer for individuals and professionals alike.
Totally 4 AI Reference Kits used in my Project
- Visual Quality Inspection
- Disease Predict
- Products Recommendation System
- Medical Imaging Diagnostics
git clone https://github.com/rppadmakumar3/Health_Assist.gitcd Health_Assistdocker-compose buildThis command will download the required Docker images and build the project.
docker-compose up