Interpretable Machine Learning Modeling for Ischemic Stroke Outcome Prediction

BACKGROUND AND PURPOSE: Mechanical thrombectomy greatly improves stroke outcomes. Nonetheless, some patients fall short of full recovery despite good reperfusion. The purpose of this study was to develop machine learning (ML) models for the pre-interventional prediction of functional outcome at 3 mo...

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Detalles Bibliográficos
Autores principales: Jabal, Mohamed Sobhi, Joly, Olivier, Kallmes, David, Harston, George, Rabinstein, Alejandro, Huynh, Thien, Brinjikji, Waleed
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Neurology
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9160988/
https://www.ncbi.nlm.nih.gov/pubmed/35665041
http://dx.doi.org/10.3389/fneur.2022.884693

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9160988/
https://www.ncbi.nlm.nih.gov/pubmed/35665041
http://dx.doi.org/10.3389/fneur.2022.884693

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