Please use this identifier to cite or link to this item:
http://hdl.handle.net/10397/109312
| Title: | Editorial : Advanced deep learning approaches for medical neuroimaging data with limitation | Authors: | Tang, Z Li, M Hu, R Dev, K |
Issue Date: | 2023 | Source: | Frontiers in computational neuroscience, 2023, v. 17, 1272448 | Keywords: | Analysis of insufficient data Brain diseases Data augmentation Data processing Neuroimaging Neuroimaging application |
Publisher: | Frontiers Research Foundation | Journal: | Frontiers in computational neuroscience | EISSN: | 1662-5188 | DOI: | 10.3389/fncom.2023.1272448 | Rights: | © 2023 Tang, Li, Hu and Dev. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) (http://creativecommons.org/licenses/by/4.0/). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. The following publication Tang Z, Li M, Hu R and Dev K (2023) Editorial: Advanced deep learning approaches for medical neuroimaging data with limitation. Front. Comput. Neurosci. 17:1272448 is available at https://doi.org/10.3389/fncom.2023.1272448. |
| Appears in Collections: | Journal/Magazine Article |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| fncom-17-1272448.pdf | 91.66 kB | Adobe PDF | View/Open |
Access
View full-text via PolyU eLinks 
Page views
19
Citations as of Nov 24, 2024
Downloads
7
Citations as of Nov 24, 2024
Google ScholarTM
Check
Altmetric
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.