Work

Machine Learning in Acute Ischemic Stroke Neuroimaging

Year: 2018

Type: review

Abstract: 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.

Source: Frontiers in Neurology

DOI: 10.3389/fneur.2018.00945

Authors: Haris Kamal, Victor Lopez, Sunil A. Sheth

Institution: The University of Texas Health Science Center at Houston

Language: English

Topic: Acute Ischemic Stroke Management

Subfield: Epidemiology

Field: Medicine

Domain: Health Sciences

SDG: Good health and well-being

Open Access status: gold

Estimated APC paid: $3,801