Machine Learning-Based Model for Predicting Incidence and Severity of Acute Ischemic Stroke in Anterior Circulation Large Vessel Occlusion

Objectives: Patients with anterior circulation large vessel occlusion are at high risk of acute ischemic stroke, which could be disabling or fatal. In this study, we applied machine learning to develop and validate two prediction models for acute ischemic stroke (Model 1) and severity of neurologica...

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Auteurs principaux:	Junzhao Cui, Jingyi Yang, Kun Zhang, Guodong Xu, Ruijie Zhao, Xipeng Li, Luji Liu, Yipu Zhu, Lixia Zhou, Ping Yu, Lei Xu, Tong Li, Jing Tian, Pandi Zhao, Si Yuan, Qisong Wang, Li Guo, Xiaoyun Liu
Format:	article
Langue:	EN
Publié:	Frontiers Media S.A. 2021
Sujets:	anterior circulation large vessel occlusion acute ischemic stroke machine learning prediction model neurological impairment Neurology. Diseases of the nervous system RC346-429
Accès en ligne:	https://doaj.org/article/f6014f0c89214bd2b22a759e6578ce2f
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Machine Learning-Based Model for Predicting Incidence and Severity of Acute Ischemic Stroke in Anterior Circulation Large Vessel Occlusion

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