Spatiotemporal feature extraction and classification of Alzheimer's disease using deep learning 3D-CNN for fMRI data.
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| Title: | Spatiotemporal feature extraction and classification of Alzheimer's disease using deep learning 3D-CNN for fMRI data. |
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| Authors: | Parmar H; Texas Tech University, Department of Electrical and Computer Engineering, Lubbock, Texas, United States., Nutter B; Texas Tech University, Department of Electrical and Computer Engineering, Lubbock, Texas, United States., Long R; National Institutes of Health, Lister Hill National Center for Biomedical Communications, National Library of Medicine, Bethesda, Maryland, United States., Antani S; National Institutes of Health, Lister Hill National Center for Biomedical Communications, National Library of Medicine, Bethesda, Maryland, United States., Mitra S; Texas Tech University, Department of Electrical and Computer Engineering, Lubbock, Texas, United States. |
| Source: | Journal of medical imaging (Bellingham, Wash.) [J Med Imaging (Bellingham)] 2020 Sep; Vol. 7 (5), pp. 056001. Date of Electronic Publication: 2020 Oct 27. |
| Publication Type: | Journal Article |
| Journal Info: | Publisher: Society of Photo-Optical Instrumentation Engineers Country of Publication: United States NLM ID: 101643461 Publication Model: Print-Electronic Cited Medium: Print ISSN: 2329-4302 (Print) Linking ISSN: 23294302 NLM ISO Abbreviation: J Med Imaging (Bellingham) Subsets: PubMed not MEDLINE |
| Database: | MEDLINE Ultimate |
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