11 citations · 20 across the 6 of their papers we have counts for
6 papers
Processing of synthetic data in AI development for healthcare and the definition of personal data in EU law
Vibeke Binz Vallevik, Anne Kjersti C. Befring, Severin Elvatun +1
Artificial intelligence (AI) has the potential to transform healthcare, but it requires access to health data. Synthetic data that is generated through machine learning models trai…
A Differentially Private Kaplan-Meier Estimator for Privacy-Preserving Survival Analysis
Narasimha Raghavan Veeraragavan, Sai Praneeth Karimireddy, Jan Franz Nygård
This paper presents a differentially private approach to Kaplan-Meier estimation that achieves accurate survival probability estimates while safeguarding individual privacy. The Ka…
Cost Reduction on Testing Evolving Cancer Registry System
Erblin Isaku, Hassan Sartaj, Christoph Laaber +4
The Cancer Registration Support System (CaReSS), built by the Cancer Registry of Norway (CRN), is a complex real-world socio-technical software system that undergoes continuous evo…
EvoCLINICAL: Evolving Cyber-Cyber Digital Twin with Active Transfer Learning for Automated Cancer Registry System
Chengjie Lu, Qinghua Xu, Tao Yue +3
The Cancer Registry of Norway (CRN) collects information on cancer patients by receiving cancer messages from different medical entities (e.g., medical labs, and hospitals) in Norw…
Automated Test Generation for Medical Rules Web Services: A Case Study at the Cancer Registry of Norway
Christoph Laaber, Tao Yue, Shaukat Ali +2
The Cancer Registry of Norway (CRN) collects, curates, and manages data related to cancer patients in Norway, supported by an interactive, human-in-the-loop, socio-technical decisi…
Generating Synthetic Data in a Secure Federated General Adversarial Networks for a Consortium of Health Registries
Narasimha Raghavan Veeraragavan, Jan Franz Nygård
In this work, we review the architecture design of existing federated General Adversarial Networks (GAN) solutions and highlight the security and trust-related weaknesses in the ex…