Composite small vessel disease scores predict hemorrhagic transformation after thrombectomy: a machine learning study.
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| Title: | Composite small vessel disease scores predict hemorrhagic transformation after thrombectomy: a machine learning study. |
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| Authors: | Goulart TO; Department of Medicine, Temerty Faculty of Medicine, University of Toronto, Toronto, ON, Canada; Department of Neurology, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, ON, Canada; Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA; Department of Neuroscience and Behavioral Sciences, Ribeirão Preto Medical School, University of São Paulo, Ribeirão Preto, São Paulo, Brazil. Electronic address: thiago.goulart@mail.utoronto.ca., do Vale Martins-Filho RK; Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA; Department of Neuroscience and Behavioral Sciences, Ribeirão Preto Medical School, University of São Paulo, Ribeirão Preto, São Paulo, Brazil., Camilo MR; Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA; Department of Neuroscience and Behavioral Sciences, Ribeirão Preto Medical School, University of São Paulo, Ribeirão Preto, São Paulo, Brazil., Abud DG; Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA; Department of Neuroscience and Behavioral Sciences, Ribeirão Preto Medical School, University of São Paulo, Ribeirão Preto, São Paulo, Brazil., Pontes-Neto OM; Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA; Department of Neuroscience and Behavioral Sciences, Ribeirão Preto Medical School, University of São Paulo, Ribeirão Preto, São Paulo, Brazil. |
| Source: | Journal of clinical neuroscience : official journal of the Neurosurgical Society of Australasia [J Clin Neurosci] 2026 Sep; Vol. 151, pp. 112098. Date of Electronic Publication: 2026 May 19. |
| Publication Type: | Journal Article |
| Journal Info: | Publisher: Churchill Livingstone Country of Publication: Scotland NLM ID: 9433352 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1532-2653 (Electronic) Linking ISSN: 09675868 NLM ISO Abbreviation: J Clin Neurosci Subsets: MEDLINE |
| Database: | MEDLINE Ultimate |
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