NateNet
NateNet is a convolutional neural network intended for image recognition for neuroimaging[1]
| Developer(s) | Nate Stern |
|---|---|
| Initial release | October 29, 2022 |
| Engine |
Search NateNet on Amazon.
Background[edit]
Since the ALEXNET convolution network did not give a good enough performance in the field, then it was decided to develop a new convolution network intended for development in the field of neuroscience.[1]
Structure[edit]
The structure of the NateNet convolutional network contains 6 convolutional layers.
Productivity[edit]
The network showed specificity of detecting schizophrenia with fMRI: 0.986 versus Shi et al., 2021 shows specificity of 0.937 only[2]
Sourcecode[3][edit]
See also[edit]
References[edit]
- ↑ 1.0 1.1 Khan, Sameer; Yong, Suet-Peng (December 2017). "A deep learning architecture for classifying medical images of anatomy object". 2017 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC). Kuala Lumpur: IEEE: 1661–1668. doi:10.1109/APSIPA.2017.8282299. ISBN 978-1-5386-1542-3. Unknown parameter
|s2cid=ignored (help) - ↑ Shi, Dafa; Li, Yanfei; Zhang, Haoran; Yao, Xiang; Wang, Siyuan; Wang, Guangsong; Ren, Ke (2021-06-09). "Machine Learning of Schizophrenia Detection with Structural and Functional Neuroimaging". Disease Markers. 2021: 9963824. doi:10.1155/2021/9963824. ISSN 0278-0240. PMC 8208855 Check
|pmc=value (help). PMID 34211615 Check|pmid=value (help). - ↑ NSH531 (2022-09-18), xschizo, retrieved 2022-10-29
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