4 citations · 9 across the 6 of their papers we have counts for
3 papers · 1 filter
Private, Efficient and Scalable Kernel Learning for Medical Image Analysis
Anika Hannemann, Arjhun Swaminathan, Ali Burak Ünal +1
Medical imaging is key in modern medicine. From magnetic resonance imaging (MRI) to microscopic imaging for blood cell detection, diagnostic medical imaging reveals vital insights…
PP-GWAS: Privacy Preserving Multi-Site Genome-wide Association Studies
Arjhun Swaminathan, Anika Hannemann, Ali Burak Ünal +2
Genome-wide association studies are pivotal in understanding the genetic underpinnings of complex traits and diseases. Collaborative, multi-site GWAS aim to enhance statistical pow…
Federated Learning in Genetics: Extended Analysis of Accuracy, Performance and Privacy Trade-offs
Anika Hannemann, Jan Ewald, Leo Seeger +1
Machine learning on large-scale genomic or transcriptomic data is important for many novel health applications. For example, precision medicine tailors medical treatments to patien…