Population-Level Digital Stroke Surveillance: Building a Fair and Accurate ICD-10 Detection Model.

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Bibliographic Details
Title: Population-Level Digital Stroke Surveillance: Building a Fair and Accurate ICD-10 Detection Model.
Authors: Esenwa C; Department of Neurology, Montefiore Health System, New York, New York, USA, cesenwa@montefiore.org., Liberman AL; Department of Neurology, Weill Cornell Medicine, Cornell University, New York, New York, USA., Cheng NT; Department of Neurology, Weill Cornell Medicine, Cornell University, New York, New York, USA., Dardick J; Department of Neurology and Neurosurgery, The Johns Hopkins Hospital, Johns Hopkins Medicine, Baltimore, Maryland, USA., Daza-Ovalle JF; Department of Neurology, Montefiore Health System, New York, New York, USA., Labovitz D; Department of Neurology, Montefiore Health System, New York, New York, USA., Lutz J; Beats Medical, Dublin, Ireland.; Chobanian and Avedisian School of Medicine, Boston University, Boston, Massachusetts, USA., Clancy C; Beats Medical, Dublin, Ireland., Ferryman K; Johns Hopkins Berman Institute of Bioethics, Johns Hopkins University, Baltimore, Maryland, USA.; Johns Hopkins Bloomberg School of Public Health, Johns Hopkins University, Baltimore, Maryland, USA.
Source: Cerebrovascular diseases (Basel, Switzerland) [Cerebrovasc Dis] 2026 Mar 20, pp. 1-7. Date of Electronic Publication: 2026 Mar 20.
Publication Type: Journal Article
Journal Info: Publisher: Karger Country of Publication: Switzerland NLM ID: 9100851 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1421-9786 (Electronic) Linking ISSN: 10159770 NLM ISO Abbreviation: Cerebrovasc Dis Subsets: MEDLINE
Database: MEDLINE Ultimate
Description
ISSN:1421-9786
DOI:10.1159/000550393