Predicting Mechanical Thrombectomy Outcome and Time Limit through ADC Value Analysis: A Comprehensive Clinical and Simulation Study Using Machine Learning

Predicting outcomes after mechanical thrombectomy (MT) remains challenging for patients with acute ischemic stroke (AIS). This study aimed to explore the usefulness of machine learning (ML) methods using detailed apparent diffusion coefficient (ADC) analysis to predict patient outcomes and simulate...

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Detalles Bibliográficos
Autores principales: Oura, Daisuke, Takamiya, Soichiro, Ihara, Riku, Niiya, Yoshimasa, Sugimori, Hiroyuki
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10340725/
https://www.ncbi.nlm.nih.gov/pubmed/37443532
http://dx.doi.org/10.3390/diagnostics13132138

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10340725/
https://www.ncbi.nlm.nih.gov/pubmed/37443532
http://dx.doi.org/10.3390/diagnostics13132138

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