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dc.contributor.authorVoigtlaender, Sebastian
dc.contributor.authorPawelczyk, Johannes
dc.contributor.authorGeiger, Mario
dc.contributor.authorVaios, Eugene J.
dc.contributor.authorKarschnia, Philipp
dc.contributor.authorCudkowicz, Merit
dc.contributor.authorDietrich, Jorg
dc.contributor.authorHaraldsen, Ira R. J. H.
dc.contributor.authorFeigin, Valery
dc.contributor.authorOwolabi, Mayowa
dc.contributor.authorWhite, Tara L.
dc.contributor.authorŚwieboda, Paweł
dc.contributor.authorFarahany, Nita
dc.date.accessioned2025-04-07T16:53:04Z
dc.date.available2025-04-07T16:53:04Z
dc.date.issued2024-02-17
dc.identifier.urihttps://hdl.handle.net/1721.1/159057
dc.description.abstractNeurological conditions are the leading cause of disability and mortality combined, demanding innovative, scalable, and sustainable solutions. Brain health has become a global priority with adoption of the World Health Organization’s Intersectoral Global Action Plan in 2022. Simultaneously, rapid advancements in artificial intelligence (AI) are revolutionizing neurological research and practice. This scoping review of 66 original articles explores the value of AI in neurology and brain health, systematizing the landscape for emergent clinical opportunities and future trends across the care trajectory: prevention, risk stratification, early detection, diagnosis, management, and rehabilitation. AI’s potential to advance personalized precision neurology and global brain health directives hinges on resolving core challenges across four pillars—models, data, feasibility/equity, and regulation/innovation—through concerted pursuit of targeted recommendations. Paramount actions include swift, ethical, equity-focused integration of novel technologies into clinical workflows, mitigating data-related issues, counteracting digital inequity gaps, and establishing robust governance frameworks balancing safety and innovation.en_US
dc.publisherSpringer Berlin Heidelbergen_US
dc.relation.isversionofhttps://doi.org/10.1007/s00415-024-12220-8en_US
dc.rightsArticle is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use.en_US
dc.sourceSpringer Berlin Heidelbergen_US
dc.titleArtificial intelligence in neurology: opportunities, challenges, and policy implicationsen_US
dc.typeArticleen_US
dc.identifier.citationVoigtlaender, S., Pawelczyk, J., Geiger, M. et al. Artificial intelligence in neurology: opportunities, challenges, and policy implications. J Neurol 271, 2258–2273 (2024).en_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Electrical Engineering and Computer Scienceen_US
dc.relation.journalJournal of Neurologyen_US
dc.eprint.versionAuthor's final manuscripten_US
dc.type.urihttp://purl.org/eprint/type/JournalArticleen_US
eprint.statushttp://purl.org/eprint/status/PeerRevieweden_US
dc.date.updated2025-03-27T13:46:49Z
dc.language.rfc3066en
dc.rights.holderThe Author(s), under exclusive licence to Springer-Verlag GmbH Germany
dspace.embargo.termsY
dspace.date.submission2025-03-27T13:46:49Z
mit.journal.volume271en_US
mit.licensePUBLISHER_POLICY
mit.metadata.statusAuthority Work and Publication Information Neededen_US


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