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A Novel Matrix-Similarity Based Loss Function for Joint Regression and Classification in AD Diagnosis
Recent studies on AD/MCI diagnosis have shown that the tasks of identifying brain disease and predicting clinical scores are highly related to each other. Furthermore, it has been shown that feature selection with a manifold learning or a sparse model can handle the problems of high feature dimensio...
Tallennettuna:
| Päätekijät: | , , |
|---|---|
| Aineistotyyppi: | Artigo |
| Kieli: | Inglês |
| Julkaistu: |
2014
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| Aiheet: | |
| Linkit: | https://ncbi.nlm.nih.gov/pmc/articles/PMC4138265/ https://ncbi.nlm.nih.gov/pubmed/24911377 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1016/j.neuroimage.2014.05.078 |
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