Machine Learning in Acute Ischemic Stroke Neuroimaging

被引：69

作者：

Kamal, Haris ^{[1
]}

Lopez, Victor ^{[1
]}

Sheth, Sunil A. ^{[1
]}

机构：

[1] Univ Texas Hlth Sci Ctr Houston, Dept Neurol, Houston, TX 77030 USA

来源：

FRONTIERS IN NEUROLOGY | 2018年 / 9卷

关键词：

stroke; neuroimaging; machine learning (artificial intelligence); neurosciences; support vector machina (SVM); stroke management; stroke diagnosis; EARLY CT SCORE; CEREBRAL EDEMA; BRAIN; CLASSIFICATION; RELIABILITY; PREDICTION; TISSUE; TIME; SCHIZOPHRENIA; THROMBECTOMY;

D O I：

10.3389/fneur.2018.00945

中图分类号：

R74 [神经病学与精神病学];

学科分类号：

摘要：

Machine Learning (ML) through pattern recognition algorithms is currently becoming an essential aid for the diagnosis, treatment, and prediction of complications and patient outcomes in a number of neurological diseases. The evaluation and treatment of Acute Ischemic Stroke (AIS) have experienced a significant advancement over the past few years, increasingly requiring the use of neuroimaging for decision-making. In this review, we offer an insight into the recent developments and applications of ML in neuroimaging focusing on acute ischemic stroke.

引用

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