Quantum machine learning project focused on breast cancer diagnostics using Qiskit and hybrid ML workflows.
This project explores the use of quantum variational circuits and hybrid quantum-classical machine learning models for breast cancer prediction and diagnostics.
The objective is to evaluate the effectiveness of quantum-enhanced models compared to traditional machine learning approaches on medical datasets.
- Quantum variational circuits
- Hybrid quantum-classical workflows
- Breast cancer dataset analysis
- Qiskit-based implementation
- Comparative evaluation with classical ML models
- Python
- Qiskit
- NumPy
- scikit-learn
- Matplotlib
✅ Dataset preprocessing completed ✅ Quantum model experimentation completed ✅ Comparative evaluation performed 🚀 Research optimization and documentation in progress