Stroke recovery phenotyping through network trajectory approaches and graph neural networks

Authors

Sanjukta Krishnagopal, University College London
Keith Lohse, Washington University School of Medicine in St. Louis
Robynne Braun, University of Maryland

Journal

Brain Informatics

Publication Date

6-19-2022

Volume

9

Issue

1

First Page

13

Document Type

Open Access Publication

DOI

10.1186/s40708-022-00160-w

Rights and Permissions

Krishnagopal, S., Lohse, K. & Braun, R. Stroke recovery phenotyping through network trajectory approaches and graph neural networks. Brain Inf. 9, 13 (2022). https://doi.org/10.1186/s40708-022-00160-w This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

Recommended Citation

Krishnagopal, Sanjukta; Lohse, Keith; and Braun, Robynne, "Stroke recovery phenotyping through network trajectory approaches and graph neural networks." Brain Informatics. 9, 1. 13 (2022).
https://digitalcommons.wustl.edu/oa_4/451