5 papers
A Multiparty Homomorphic Encryption Approach to Confidential Federated Kaplan Meier Survival Analysis
Narasimha Raghavan Veeraragavan, Svetlana Boudko, Jan Franz Nygård
The proliferation of real-world health data enables multi-institutional survival studies, yet privacy constraints preclude centralizing sensitive records. We present a privacy-pres…
Assessing Quantum Extreme Learning Machines for Software Testing in Practice
Asmar Muqeet, Hassan Sartaj, Aitor Arrieta +6
Machine learning has been extensively applied for classical software testing activities such as test generation, minimization, and prioritization. Along the same lines, there has b…
Federated Survival Analysis with Node-Level Differential Privacy: Private Kaplan-Meier Curves
Narasimha Raghavan Veeraragavan, Jan Franz Nygård
We investigate how to calculate Kaplan-Meier survival curves across multiple health-care jurisdictions while protecting patient privacy with node-level differential privacy. Each s…
Can One Safety Loop Guard Them All? Agentic Guard Rails for Federated Computing
Narasimha Raghavan Veeraragavan, Jan Franz Nygård
We propose Guardian-FC, a novel two-layer framework for privacy preserving federated computing that unifies safety enforcement across diverse privacy preserving mechanisms, includi…
Quantum Neural Network Classifier for Cancer Registry System Testing: A Feasibility Study
Xinyi Wang, Shaukat Ali, Paolo Arcaini +2
The Cancer Registry of Norway (CRN) is a part of the Norwegian Institute of Public Health (NIPH) and is tasked with producing statistics on cancer among the Norwegian population. F…