Proceedings - International Symposium on Biomedical Imaging 
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This is an RSS file. You can use it to subscribe to this data in your favourite RSS reader or to display this data on your own website or blog.Hierarchical brain embedding using explainable graph learning
Proc IEEE Int Symp Biomed Imaging. 2022 Mar;2022:10.1109/isbi52829.2022.9761543. doi: 10.1109/isbi52829.2022.9761543. Epub 2022 Apr 26.ABSTRACTBrain networks have been extensively studied in neuroscience, to better understand human behavior, and to identify and characterize distributed brain abnormalities in neurological and psychiatric conditions. Several deep graph learning models have been proposed for brain network analysis, yet most current models lack interpretability, which makes it hard to gain any heuristic biological insights into the results. In this paper, we propose a new explainable graph learning model, name...
Source: Proceedings - International Symposium on Biomedical Imaging - January 23, 2023 Category: Radiology Authors: Haoteng Tang Lei Guo Xiyao Fu Benjamin Qu Paul M Thompson Heng Huang Liang Zhan Source Type: research
