| Title | A Multi-modal Clinical Dataset for Critically-Ill and Premature Infant Monitoring: EEG and Videos |
| Author | |
| DOI | |
| Publication Years | 2022
|
| ISSN | 2641-3590
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| ISBN | 978-1-6654-8792-4
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| Source Title | |
| Pages | 1-5
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| Conference Date | 27-30 Sept. 2022
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| Conference Place | Ioannina, Greece
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| Keywords | |
| SUSTech Authorship | First
|
| URL | [Source Record] |
| Data Source | IEEE
|
| PDF url | https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=9926840 |
| Citation statistics |
Cited Times [WOS]:0
|
| Document Type | Conference paper |
| Identifier | http://kc.sustech.edu.cn/handle/2SGJ60CL/412118 |
| Department | Department of Biomedical Engineering |
| Affiliation | 1.Department of Biomedical Engineering, Southern University of Science and Technology, China 2.Neonatal Intensive Care Unit, Nanfang Hospital of Southern Medical University, China |
| First Author Affilication | Department of Biomedical Engineering |
| First Author's First Affilication | Department of Biomedical Engineering |
| Recommended Citation GB/T 7714 |
Yongshen Zeng,Xiaoyan Song,Hongwu Chen,et al. A Multi-modal Clinical Dataset for Critically-Ill and Premature Infant Monitoring: EEG and Videos[C],2022:1-5.
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| Files in This Item: | There are no files associated with this item. | |||||
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