AI in Neurology Selected Applications, Evidence Maturity, and Governance for Latin America

Abstract

This whitepaper examines selected artificial intelligence applications in neurology: stroke imaging and workflow, EEG and epilepsy, multimodal dementia assessment, movement analysis, multiple-sclerosis follow-up, and document synthesis. Evidence maturity is uneven. The corpus contains retrospective development, reviews, and technical comparisons, but little direct demonstration of prospective utility, outcome impact, or routine implementation. Stroke imaging has the most developed operational pathway within this corpus; this does not establish general clinical benefit or authorize independent diagnosis. For EEG, dementia, and other domains, support for review or data integration is better established than replacement of specialist judgment. For Latin America, the regional sources identified document inequalities in stroke-care networks and cross-cutting conditions involving infrastructure, interoperability, connectivity, and governance. They do not demonstrate neurological-AI performance in the region. Operational implications are therefore labeled as author implementation inferences and require local validation. A retrospective metric alone is insufficient: before changing care, teams must define the task, human respons