Small vessel disease burden predicts functional outcomes in patients with acute ischemic stroke using machine learning

Aims Our purpose is to assess the role of cerebral small vessel disease (SVD) in prediction models in patients with different subtypes of acute ischemic stroke (AIS). Methods We enrolled 398 small‐vessel occlusion (SVO) and 175 large artery atherosclerosis (LAA) AIS patients. Functional outcomes wer...

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Bibliographic Details
Published in:	CNS neuroscience & therapeutics Vol. 29; no. 4; pp. 1024 - 1033
Main Authors:	Wang, Xueyang, Lyu, Jinhao, Meng, Zhihua, Wu, Xiaoyan, Chen, Wen, Wang, Guohua, Niu, Qingliang, Li, Xin, Bian, Yitong, Han, Dan, Guo, Weiting, Yang, Shuai, Bian, Xiangbing, Lan, Yina, Wang, Liuxian, Duan, Qi, Zhang, Tingyang, Duan, Caohui, Tian, Chenglin, Chen, Ling, Lou, Xin
Format:	Journal Article
Language:	English
Published:	England John Wiley & Sons, Inc 01-04-2023 John Wiley and Sons Inc
Subjects:	acute ischemic stroke Algorithms Arteriosclerosis Atherosclerosis Cardiac arrhythmia Cardiovascular disease Cerebral blood flow cerebral small vessel disease Cerebral Small Vessel Diseases - complications Cerebral Small Vessel Diseases - diagnostic imaging Cost of Illness Decision trees Hospitals Humans Hyperglycemia Hyperlipidemia Hypertension Ischemia Ischemic Stroke - diagnostic imaging Ischemic Stroke - therapy Learning algorithms Machine Learning Magnetic resonance imaging Medical imaging Methods Neuroimaging Original prediction model Prediction models Prognosis Software Stroke Stroke - diagnostic imaging Stroke - therapy Substantia alba Vascular diseases Veins & arteries cerebral small vessel disease prediction model machine learning acute ischemic stroke
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