Performance Analysis of Machine Learning and Deep Learning Architectures on Early Stroke Detection Using Carotid Artery Ultrasound Images.
Atherosclerotic plaque deposit in the carotid artery is used as an early estimate to identify the presence of cardiovascular diseases. Ultrasound images of the carotid artery are used to provide the extent of stenosis by examining the intima-media thickness and plaque diameter. A total of 361 images...
| Publicado en: | Frontiers in Aging Neuroscience Vol. 14; pp. 1 - 13 |
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| Autores principales: | , , , , |
| Formato: | computer program diagnostic images equations & formulas research tables/charts Journal Article |
| Publicado: |
Frontiers Media S.A.
1/27/2022
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=154923064&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 154923064 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 16634365 BG2U jtl: Frontiers in Aging Neuroscience issn: 16634365 maglogo: N pubinfo: dt: 1/27/2022 vid: 14 pid: 40038 pub: Frontiers Media S.A. artinfo: ui: 154923064 154923064 154923064 10.3389/fnagi.2021.828214 154923064 ppf: 1 ppct: 12 formats: tig: atl: Performance Analysis of Machine Learning and Deep Learning Architectures on Early Stroke Detection Using Carotid Artery Ultrasound Images. aug: au: Latha, S. Muthu, P. Lai, Khin Wee Khalil, Azira Dhanalakshmi, Samiappan affil: Department of Electronics and Communication Engineering, SRM Institute of Science and Technology, Chennai, India sug: subj: Machine Learning Deep Learning Early Diagnosis Methods Stroke Diagnosis Carotid Arteries Ultrasonography Image Interpretation, Computer Assisted Methods Human Carotid Intima-Media Thickness Decision Trees Random Forest Logistic Regression Algorithms Neural Networks (Computer) Funding Source ab: Atherosclerotic plaque deposit in the carotid artery is used as an early estimate to identify the presence of cardiovascular diseases. Ultrasound images of the carotid artery are used to provide the extent of stenosis by examining the intima-media thickness and plaque diameter. A total of 361 images were classified using machine learning and deep learning approaches to recognize whether the person is symptomatic or asymptomatic. CART decision tree, random forest, and logistic regression machine learning algorithms, convolutional neural network (CNN), Mobilenet, and Capsulenet deep learning algorithms were applied in 202 normal images and 159 images with carotid plaque. Random forest provided a competitive accuracy of 91.41% and Capsulenet transfer learning approach gave 96.7% accuracy in classifying the carotid artery ultrasound image database. pubtype: Academic Journal doctype: computer program diagnostic images equations & formulas research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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