A deep learning-based system for automatic detection of emesis with high accuracy in Suncus murinus
Abstract Quantifying emesis in Suncus murinus (S. murinus) has traditionally relied on direct observation or reviewing recorded behaviour, which are laborious, time-consuming processes that are susceptible to operator error. With rapid advancements in deep learning, automated animal behaviour quanti...
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| Main Authors: | Zengbing Lu, Yimeng Qiao, Xiaofei Huang, Dexuan Cui, Julia Y. H. Liu, Man Piu Ngan, Luping Liu, Zhixin Huang, Zi-Tong Li, Lingqing Yang, Aleena Khalid, Yingyi Deng, Sze Wa Chan, Longlong Tu, John A. Rudd |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2025-02-01
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| Series: | Communications Biology |
| Online Access: | https://doi.org/10.1038/s42003-025-07479-0 |
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