Comparison of Cubic SVM with Gaussian SVM: Classification of Infarction for detecting Ischemic Stroke

9th Annual Basic Science International Conference 2019

自然科学（总论）

Bagasta, Amanda Rizki^1 ; Rustam, Zuherman^1 ; Pandelaki, Jacub^2 ; Nugroho, Widyo Ari^2

Department of Mathematics, FMIPA Universitas Indonesia, Kampus UI Depok, Depok

16424, Indonesia^1

Medical Department of Radiology, RSUPN Dr. Cipto Mangunkusumo, Kota Jakarta Pusat, DKI, Jakarta

10430, Indonesia^2

关键词: Accurate performance;    Blood flow;    Blood supply;    Brain tissue;    Functional information;    Gaussians;    Ischemic strokes;   

Others  :  https://iopscience.iop.org/article/10.1088/1757-899X/546/5/052016/pdf
DOI  :  10.1088/1757-899X/546/5/052016

学科分类：自然科学（综合）

来源: IOP

【 摘 要 】

Ischemic Stroke is a condition whereby the blood supply to the brain is disrupted or reduced due to a blockage and if it is not treated immediately will cause the death of the brain. A decrease in blood flow resulting in dead brain tissue can be called an infarction. The classifications of infarction help the health sector in detecting ischemic stroke in patients. In medicine, CT scans can be used to identify Infarctions and for detecting Ischemic Stroke in patients. Therefore, studying the CT scans is crucial in helping doctors obtain functional information about the surrounding brain tissues which will be used for detecting infarction in the brain. Since it is important to pay more attention at the time of choosing the best method that gives the best results, therefore this study proposes to compare between two types of methods, Gaussian Support Vector Machine (Gaussian SVM) and Cubic Support Vector Machine (Cubic SVM). The Cubic SVM could be an efficient method for infarction classification with accurate performances as high as 80%.