Hybrid Quantum-Classical Intelligence for Personalized Smart Healthcare Systems
Aravindhan Surendar, Robbi Rahim, Shaik Sadulla
Hybrid quantum-classical intelligence is a new promising paradigm to develop personalized smart healthcare systems with exemplification of computational power of quantum computing and scalability of classical artificial intelligent. This chapter introduces a hybrid design based on quantum machine learning, healthcare analytics, explainable AI, federated learning, and intelligent clinical decision support to apply precision medicine via this design. The given architecture will allow analyzing multimodal healthcare data efficiently, predicting the disease-risk, optimizing treatment plans on a personal scale, interpreting medical images, and predictive healthcare analytics. The framework enables the next-generation smart healthcare ecosystems by improving the computational efficiency, decision accuracy, transparency, and preserving privacy to enhance the realization of intelligent, patient-centric healthcare services.
Advances in computational intelligence and robotics book series•Oct 23, 2026•0 citations