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A Review of Computational Methods to Predict the Risk of Rupture of Abdominal Aortic Aneurysms
Joint Authors
Ng, Eddie Y. K.
Canchi, Tejas
Kumar, S. D.
Narayanan, Sriram
Source
Issue
Vol. 2015, Issue 2015 (31 Dec. 2015), pp.1-12, 12 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2015-10-05
Country of Publication
Egypt
No. of Pages
12
Main Subjects
Abstract EN
Computational methods have played an important role in health care in recent years, as determining parameters that affect a certain medical condition is not possible in experimental conditions in many cases.
Computational fluid dynamics (CFD) methods have been used to accurately determine the nature of blood flow in the cardiovascular and nervous systems and air flow in the respiratory system, thereby giving the surgeon a diagnostic tool to plan treatment accordingly.
Machine learning or data mining (MLD) methods are currently used to develop models that learn from retrospective data to make a prediction regarding factors affecting the progression of a disease.
These models have also been successful in incorporating factors such as patient history and occupation.
MLD models can be used as a predictive tool to determine rupture potential in patients with abdominal aortic aneurysms (AAA) along with CFD-based prediction of parameters like wall shear stress and pressure distributions.
A combination of these computer methods can be pivotal in bridging the gap between translational and outcomes research in medicine.
This paper reviews the use of computational methods in the diagnosis and treatment of AAA.
American Psychological Association (APA)
Canchi, Tejas& Kumar, S. D.& Ng, Eddie Y. K.& Narayanan, Sriram. 2015. A Review of Computational Methods to Predict the Risk of Rupture of Abdominal Aortic Aneurysms. BioMed Research International،Vol. 2015, no. 2015, pp.1-12.
https://search.emarefa.net/detail/BIM-1057047
Modern Language Association (MLA)
Canchi, Tejas…[et al.]. A Review of Computational Methods to Predict the Risk of Rupture of Abdominal Aortic Aneurysms. BioMed Research International No. 2015 (2015), pp.1-12.
https://search.emarefa.net/detail/BIM-1057047
American Medical Association (AMA)
Canchi, Tejas& Kumar, S. D.& Ng, Eddie Y. K.& Narayanan, Sriram. A Review of Computational Methods to Predict the Risk of Rupture of Abdominal Aortic Aneurysms. BioMed Research International. 2015. Vol. 2015, no. 2015, pp.1-12.
https://search.emarefa.net/detail/BIM-1057047
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1057047