7 citations · 20 across the 11 of their papers we have counts for
4 papers · 1 filter
Secure Neuroimaging Analysis using Federated Learning with Homomorphic Encryption
Dimitris Stripelis, Hamza Saleem, Tanmay Ghai +8
Federated learning (FL) enables distributed computation of machine learning models over various disparate, remote data sources, without requiring to transfer any individual data to…
Membership Inference Attacks on Deep Regression Models for Neuroimaging
Umang Gupta, Dimitris Stripelis, Pradeep K. Lam +3
Ensuring the privacy of research participants is vital, even more so in healthcare environments. Deep learning approaches to neuroimaging require large datasets, and this often nec…
Scaling Neuroscience Research using Federated Learning
Dimitris Stripelis, Jose Luis Ambite, Pradeep Lam +1
The amount of biomedical data continues to grow rapidly. However, the ability to analyze these data is limited due to privacy and regulatory concerns. Machine learning approaches t…
Improved Brain Age Estimation with Slice-based Set Networks
Umang Gupta, Pradeep K. Lam, Greg Ver Steeg +1
Deep Learning for neuroimaging data is a promising but challenging direction. The high dimensionality of 3D MRI scans makes this endeavor compute and data-intensive. Most conventio…