Quantum Computing for Biomedical Intelligence and Secure Systems

Abstract: Quantum computing offers new approaches for analyzing complex biomedical data while also raising important questions about security and trust. This talk presents our recent work at the intersection of quantum machine learning, biomedical intelligence, and secure quantum systems. We discuss hybrid quantum machine learning for stress and emotion recognition, feature selection from physiological signals, tamper detection in biomedical data, and Alzheimer's disease screening from MRI scans. The talk then examines security threats to quantum machine learning systems, including crosstalk-induced and quantum Trojan-style attacks, and highlights the need for secure-by-design quantum computing. Overall, the talk explores both the opportunities of quantum computing for biomedical intelligence and the security challenges that must be addressed for real-world deployment.