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• W2183651106 abstract "One of the most communal causes of death in the world and the foremost cause of severe, long-standing disability is Ischemic Stroke. There is an imperative need for automated techniques and mechanisms to pre diagnose people at high risk of ischemic stroke. Genetics as well as phenotypes of the visible symptoms contribute highly to the risk of stroke. There is a compelling need of post analysis and follow up checkups to prevent further strokes. A lot of research is being carried out on computer based automated techniques and mechanisms for estimation of Ischemic Stroke risk evaluation. A comparative study of different Carotid Imaging Techniques is being reported in this paper. Also the Work done by different researchers to estimate the Ischemic Stroke risk by using different feature sets is also reviewed. In depth knowledge of the preprocessing involved before actual analysis to achieve the results is also covered. Carotid Artery morphology, noise and artifacts in the Carotid images can lead to false classification. Historical patterns can facilitate improvement and accuracy of the risk evaluation. Genes trees can help take into account the genetic risk factors and gene mutations. The historical patterns can be extracted using these trees from the sampled group of data. Keeping these facts in view, we have also proposed an improved classification model for estimation of Ischemic Stroke risk. This model considers the Carotid Image Features and the Genetic Features. (Tauseef H, Fahiem MA, Farhan S, Tahir F. A Review of Image and Phylogenetic Analysis Based Techniques for Ischemic Stroke Risk Estimation. Life Sci J 2013;10(7s):1040-1049) (ISSN:1097-8135). http://www.lifesciencesite.com. 167" @default.
• W2183651106 created "2016-06-24" @default.
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• W2183651106 date "2013-01-01" @default.
• W2183651106 modified "2023-09-27" @default.
• W2183651106 title "A Review of Image and Phylogenetic Analysis Based Techniques for Ischemic Stroke Risk Estimation" @default.
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