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Artificial Intelligence in Neurology: Opportunities, Challenges, and Policy Implications

aut.relation.journalJournal of Neurology
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 RJ Hebold
dc.contributor.authorFeigin, Valery
dc.contributor.authorOwolabi, Mayowa
dc.contributor.authorWhite, Tara L
dc.contributor.authorŚwieboda, Paweł
dc.contributor.authorFarahany, Nita
dc.contributor.authorNatarajan, Vivek
dc.contributor.authorWinter, Sebastian F
dc.date.accessioned2026-03-01T21:43:46Z
dc.date.available2026-03-01T21:43:46Z
dc.date.issued2024-02-17
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.
dc.identifier.citationJournal of Neurology, ISSN: 0340-5354 (Print); 0340-5354 (Online), Springer. doi: 10.1007/s00415-024-12220-8
dc.identifier.doi10.1007/s00415-024-12220-8
dc.identifier.issn0340-5354
dc.identifier.issn0340-5354
dc.identifier.urihttp://hdl.handle.net/10292/20695
dc.languageeng
dc.publisherSpringer
dc.relation.urihttps://link.springer.com/article/10.1007/s00415-024-12220-8
dc.rightsThis is the Author's Accepted Manuscript of an article published in the Journal of Neurology © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany 2024. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
dc.rights.accessrightsOpenAccess
dc.subjectArtificial intelligence
dc.subjectBrain health
dc.subjectDigital health
dc.subjectFuture trends
dc.subjectMachine learning
dc.subjectNeurology
dc.subjectPolicy
dc.subject1103 Clinical Sciences
dc.subject1109 Neurosciences
dc.subjectNeurology & Neurosurgery
dc.subject3202 Clinical sciences
dc.subject3209 Neurosciences
dc.titleArtificial Intelligence in Neurology: Opportunities, Challenges, and Policy Implications
dc.typeJournal Article
pubs.elements-id539033

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