serikalisack/TambuaHealth

AI-powered web application designed to assist in the detection of diseases from medical images such as X-rays and MRIs. It aims to support healthcare providers with faster, accurate, and scalable diagnostic tools, especially in low-resource settings. # TambuaHealth **AI-powered multi-disease prediction system** TambuaHealth is a powerful diagnostic platform that helps detect heart disease, diabetes, breast cancer, and lung cancer using patient medical data and imagery. It’s designed with simplicity and accessibility in mind, especially for under-resourced healthcare settings. With the power of machine learning and a clean, user-friendly interface, TambuaHealth brings faster, scalable, and smarter diagnosis to the forefront of modern care. --- ## 📚 Table of Contents - ✨ Key Features - 🛠️ Tech Stack - 🧠 Disease Prediction Models - ⚙️ How It Works - 📁 File Structure - 📸 Screenshots - 🚀 Future Roadmap - 📜 License --- ## ✨ Key Features ### 🛡️ Secure Access - **User Authentication:** Secured registration and Login Pages. ### 🔍 Multi-Modal Prediction - Manual entry or prescription scan with **regex auto-fill** - Medical image upload (X-ray, CT, MRI) for deep learning inference ### 📊 Clinical Tools - Instant AI-generated reports in downloadable **PDF format** - Real-time feedback via **React Toast notifications** - All models execute directly in the backend (Node.js only — no Flask!) --- ## 🛠️ Tech Stack ### 💻 Frontend - React (Vite) + Context API - Tailwind CSS - React Leaflet *(for future geolocation analytics)* - React Toastify *(notification system)* ### 🧪 Backend - Node.js + Express - MongoDB (Atlas or Local) - Cloudinary (image storage) - Node.js Child Process (to call Python ML models) ### 🤖 Machine Learning - **Heart Disease**: Logistic Regression - **Diabetes**: Support Vector Machine (SVM) - **Breast Cancer**: CNN - **Lung Cancer**: InceptionResNet - All models trained in Python and executed via backend integration --- ## 🧠 Disease Prediction Models ----------------------------------------------------------------------------------------------- | Condition | Model | Input Type | Key Features Scanned | |-------------------|---------------------|------------- …