Interpretable machine learning for prediction of clinical outcomes in acute ischemic stroke

Interpretable machine learning for prediction of clinical outcomes in acute ischemic stroke

Background and aimsPredicting the prognosis of acute ischemic stroke (AIS) is crucial in a clinical setting for establishing suitable treatment plans. This study aimed to develop and validate a machine learning (ML) model that predicts the functional outcome of AIS patients and provides interpretabl...

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Bibliographic Details
Main Authors: Joonwon Lee, Kang Min Park, Seongho Park
Format: Article
Language:English
Published: Frontiers Media S.A. 2023-09-01
Series:Frontiers in Neurology
Subjects:
machine learning
stroke
cerebral infarction
explainable artificial intelligence
prediction
functional outcome
Online Access:https://www.frontiersin.org/articles/10.3389/fneur.2023.1234046/full

Internet

https://www.frontiersin.org/articles/10.3389/fneur.2023.1234046/full

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