DAMNet: Dynamic Mobile Architectures for Alzheimer's Disease

DAMNet: Dynamic Mobile Architectures for Alzheimer's Disease | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article DAMNet: Dynamic Mobile Architectures for Alzheimer's Disease Nan Wan This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4367823/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted You are reading this latest preprint version Abstract Alzheimer's disease (AD) presents a significant challenge in healthcare, highlighting the necessity for early and precise diagnostic tools. Our model, DAMNet, processes multi-dimensional AD data effectively, utilizing only 7.4 million parameters to achieve diagnostic accuracies of 98.3% in validation and 99.9% in testing phases. Despite a 20% pruning rate, DAMNet maintains consistent performance with less than 0.2% loss in accuracy. The model also excels in handling 3D (Three-Dimensional) MRI data, achieving a 95.7% F1 score within 805 seconds during a rigorous three-fold validation over 200 epochs. Furthermore, we introduce a novel parallel intelligent framework for early AD detection that improves feature extraction and incorporates advanced data management and control. This framework sets a new benchmark in intelligent, precise medical diagnostics, adeptly managing both 2D (Two-Dimensional) and 3D imaging data. Health sciences/Diseases/Neurological disorders/Dementia/Alzheimer's disease Health sciences/Diseases Alzheimer's Disease DAMNet 2D and 3D Imaging Parallel Intelligence Full Text Additional Declarations There is NO Competing Interest. Supplementary Files Supplementary.pdf Supplementary Figure 1-6;Supplementary Table 1-10 Cite Share Download PDF Status: Under Review Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4367823","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":304043901,"identity":"52b441d8-0fd3-47f8-9b8c-a601bab0eef3","order_by":0,"name":"Nan Wan","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAvklEQVRIiWNgGAWjYPACGyjNRryWNNK1HCZBi8Hxs8ce/NxxPnG72OEHDB/KDjPwz24goOVMXrph75nbiTtnpxkwzjh3mEHizgH8WswO5JhJ8Lbdzt1wO4eBmbftMIOBRAIBLeffmEn+bTsH0fKXKC03csykedsOQLQwEqPF/sYbM2nZtuT6DbfTDA72nEvnkbhBQItkf46Z5Ns2O2OD28kPH/wos5bjn0FACwo4AMQ8JKgfBaNgFIyCUYALAADFk0StK+MJnwAAAABJRU5ErkJggg==","orcid":"https://orcid.org/0009-0008-8547-848X","institution":"Wannan Medical College","correspondingAuthor":true,"prefix":"","firstName":"Nan","middleName":"","lastName":"Wan","suffix":""}],"badges":[],"createdAt":"2024-05-04 09:50:30","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4367823/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4367823/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":58791793,"identity":"70a2b83b-0d73-4dbb-abe4-e16b2081ea28","added_by":"auto","created_at":"2024-06-21 07:24:18","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":979718,"visible":true,"origin":"","legend":"","description":"","filename":"Manuscriptd1.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4367823/v1_covered_41470912-cf55-4a23-b441-ac81533649ad.pdf"},{"id":58791113,"identity":"df28f441-db6e-4789-9eed-e82bb24723f5","added_by":"auto","created_at":"2024-06-21 07:16:17","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":493240,"visible":true,"origin":"","legend":"\u003cp\u003eSupplementary Figure 1-6;Supplementary Table 1-10\u003c/p\u003e","description":"","filename":"Supplementary.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4367823/v1/5774f4c74bd6046da8c488f4.pdf"}],"financialInterests":"There is \u003cb\u003eNO\u003c/b\u003e Competing Interest.","formattedTitle":"DAMNet: Dynamic Mobile Architectures for Alzheimer's Disease","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":true,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":true,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"nature-portfolio","isNatureJournal":true,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"","title":"Nature Portfolio","twitterHandle":"","acdcEnabled":false,"dfaEnabled":false,"editorialSystem":"ejp","reportingPortfolio":"","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Alzheimer's Disease, DAMNet, 2D and 3D Imaging, Parallel Intelligence","lastPublishedDoi":"10.21203/rs.3.rs-4367823/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4367823/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eAlzheimer's disease (AD) presents a significant challenge in healthcare, highlighting the necessity for early and precise diagnostic tools. 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