Name
Title | ||
|---|---|---|
Multi-site fMRI Analysis Using Privacy-preserving Federated Learning and Domain Adaptation: ABIDE Results |
Abstract | ||
|---|---|---|
•A novel framework for multi-site fMRI analysis without data-sharing using privacy-preserving federated learning.•The first employment of domain adaptation techniques on federated learning formulation for medical image analysis.•Comparisons to baseline strategies and innovative model evaluation methods from the biomarker interpretation perspective.•New insights into utilizing multi-site medical data to improve both tasks performance and replicable and informative biomarker detection.•Potential solution to training deep learning models on multiple small, heterogeneous, privacy-sensitive medical datasets. |
Year | DOI | Venue |
|---|---|---|
2020 | 10.1016/j.media.2020.101765 | Medical Image Analysis |
Keywords | DocType | Volume |
Federated learning,Domain adaptation,Data sharing,Privacy,Rs-fmri,ABIDE | Journal | 65 |
ISSN | Citations | PageRank |
1361-8415 | 7 | 0.68 |
References | Authors | |
1 | 6 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Xiaoxiao Li | 1 | 30 | 6.20 |
| Gu Yufeng | 2 | 7 | 0.68 |
| Nicha C Dvornek | 3 | 21 | 9.24 |
| Lawrence H Staib | 4 | 1129 | 159.56 |
| Pamela Ventola | 5 | 22 | 5.20 |
| James S. Duncan | 6 | 2973 | 466.48 |