Name
Abstract | ||
|---|---|---|
•Predictive, subnetwork-based machine learning model for connectome data.•Novel connectivity and backbone network priors regularize model.•Approach validated on 168 structural connectomes and 1013 functional connectomes.•Proposed priors outperform all other competing methods on prediction tasks.•Resulting subnetworks are well connected and anatomically plausible. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1016/j.compmedimag.2018.08.009 | Computerized Medical Imaging and Graphics |
Keywords | Field | DocType |
Connectome,Machine learning,Subnetwork,Prediction,Brain | Autism,Computer vision,Diffusion MRI,Pattern recognition,Connectome,Human Connectome,Artificial intelligence,Prior probability,Cognition,Backbone network,Medicine,Subnetwork | Journal |
Volume | ISSN | Citations |
71 | 0895-6111 | 1 |
PageRank | References | Authors |
0.37 | 22 | 8 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Colin J. Brown | 1 | 84 | 6.12 |
| Steven P. Miller | 2 | 2 | 2.41 |
| Brian G. Booth | 3 | 88 | 7.30 |
| Jill G. Zwicker | 4 | 56 | 3.81 |
| Ruth E. Grunau | 5 | 61 | 4.98 |
| Anne R. Synnes | 6 | 2 | 1.10 |
| Vann Chau | 7 | 83 | 6.09 |
| Ghassan Hamarneh | 8 | 1353 | 110.14 |