Qu-Alz 🧠⚛️

Quantum-Enhanced Alzheimer's Prediction & Early Risk Assessment

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🚀 Demo

Click the badge above to see the project in action.

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📖 About

Qu-Alz is a cutting-edge healthcare solution that leverages Quantum Machine Learning (QML) and deep learning to provide early detection and risk assessment for Alzheimer's disease.

By introducing the Quantum Entanglement Entropy Score (EES)—a fundamentally quantum-only biomarker—this project identifies subtle patterns in MRI data that classical machine learning kernels cannot compute. This innovation aims to push the boundaries of early neurodegenerative disease diagnosis using the power of quantum information theory.

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🛠️ Tech Stack

Frontend (Interface)

• Framework: Next.js 15, React 19, TypeScript
• Styling: Tailwind CSS, Radix UI (shadcn/ui), Lucide Icons
• Visualizations: Recharts (Interactive heatmap & entanglement meters)

AI & Quantum (Backend/Models)

• Deep Learning: PyTorch (CNN for classification, U-Net for MRI segmentation)
• Quantum Computing: Qiskit (Quantum circuits, ZZFeatureMap, density matrices)
• Scientific Computing: NumPy, SciPy, Scikit-Learn
• Visualization: Matplotlib, Seaborn

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✨ Features

• 🧬 Quantum-Only Biomarker: Computes Entanglement Entropy Score (EES) using quantum superposition and density matrices.
• 🖼️ MRI Segmentation: Automated U-Net based segmentation of brain regions from MRI scans.
• 📊 Disease Classification: Multi-stage Alzheimer's classification (No Impairment, Very Mild, Mild, Moderate).
• 📈 Risk Pipeline: Comprehensive pipeline integrating classical features with quantum biomarkers for risk assessment.
• 🖥️ Interactive Dashboard: A professional clinical interface for uploading MRIs and visualizing diagnostic results.

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📂 Project Structure

• interface/: Next.js web application for clinical triage.
• classifier/: CNN and QCNN (Quantum CNN) models for Alzheimer's stage prediction.
• segmentation/: U-Net models and scripts for automated brain MRI segmentation.
• quantum-risk/: Quantum EES (Entanglement Entropy Score) pipeline and risk assessment.
• docs/: Project documentation, presentation materials, and diagnostic results.

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🚦 Getting Started

1. Web Interface

cd interface
npm install --legacy-peer-deps
npm run dev

2. Quantum & AI Models

cd quantum-risk
pip install -r requirements.txt
python test_quantum_ees.py

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📜 License

This project is licensed under the MIT License.

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Originally developed for the SEA Quantathon 2025 (Healthcare & Medicine Track) by Team The Qure.