AI Article Synopsis
- Machine Learning is playing a crucial role in diagnosing and predicting outcomes for neurological diseases, particularly in Acute Ischemic Stroke (AIS).
- Recent advancements have enhanced the use of neuroimaging in making treatment decisions for AIS.
- This review highlights the latest developments and applications of machine learning techniques specifically related to neuroimaging in the context of acute ischemic stroke.
Article 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.
Download full-text PDF |
Source |
|---|---|
| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6236025 | PMC |
| http://dx.doi.org/10.3389/fneur.2018.00945 | DOI Listing |
Publication Analysis
Top Keywords
acute ischemic
12
ischemic stroke
12
machine learning
8
learning acute
4
stroke neuroimaging
4
neuroimaging machine
4
learning pattern
4
pattern recognition
4
recognition algorithms
4
algorithms currently
4
Similar Publications
Want AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!