An intelligent magnetic resonance imagining-based multistage Alzheimer's disease classification using swish-convolutional neural networks.
| Publicado en: | Medical & Biological Engineering & Computing Vol. 63; no. 3; pp. 885 - 900 |
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| Autores principales: | , |
| Formato: | Journal Article |
| Publicado: |
Springer Nature
Mar2025
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=183577110&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 183577110 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 01400118 PO0 jtl: Medical & Biological Engineering & Computing issn: 01400118 maglogo: N pubinfo: dt: Mar2025 vid: 63 iid: 3 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 183577110 180880661 10.1007/s11517-024-03237-2 183577110 ppf: 885 ppct: 15 formats: fmt: – @attributes: type: T – @attributes: type: P tig: atl: An intelligent magnetic resonance imagining-based multistage Alzheimer's disease classification using swish-convolutional neural networks. aug: au: B., Archana Kalirajan, K. affil: https://ror.org/01qhf1r47 Department of Electronics and Communication Engineering, KGiSL Institute of Technology, Coimbatore, Tamil Nadu, India sug: pubtype: Academic Journal doctype: Journal Article ougenre: Article ab: language: English refInfo: holdings: @attributes: islocal: N |
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