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Performance Analysis of Machine Learning and Deep Learning Architectures on Early Stroke Detection Using Carotid Artery Ultrasound Images

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dc.contributor.authorS. Lathaen_US
dc.contributor.authorP. Muthuen_US
dc.contributor.authorKhin Wee Laien_US
dc.contributor.authorAzira Khalilen_US
dc.contributor.authorSamiappan Dhanalakshmien_US
dc.date.accessioned2024-05-29T02:26:35Z
dc.date.available2024-05-29T02:26:35Z
dc.date.issued2022
dc.date.submitted2023-1-10
dc.descriptionVolume 13en_US
dc.description.abstractAtherosclerotic 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.en_US
dc.identifier.citationLatha S, Muthu P, Lai KW, Khalil A and Dhanalakshmi S (2022) Performance Analysis of Machine Learning and Deep Learning Architectures on Early Stroke Detection Using Carotid Artery Ultrasound Images. Front. Aging Neurosci. 13:828214. doi: 10.3389/fnagi.2021.828214en_US
dc.identifier.doi10.3389/fnagi.2021.828214
dc.identifier.epage12
dc.identifier.issn1663-4365
dc.identifier.issueSI
dc.identifier.spage1
dc.identifier.urihttps://www.frontiersin.org/articles/10.3389/fnagi.2021.828214/full
dc.identifier.urihttps://www.scopus.com/record/display.uri?eid=2-s2.0-85124574338&origin=resultslist&sort=plf-f&src=s&sid=ff7b2cafb526bfeca0fe6ae95dfa2def&sot=b&sdt=b&s=TITLE-ABS-KEY%28Performance+Analysis+Of+Machine+Learning+And+Deep+Learning+Architectures+On+Early+Stroke+Detection+Using+Carotid+Artery+Ultrasound+Images%29&sl=113&sessionSearchId=ff7b2cafb526bfeca0fe6ae95dfa2def
dc.identifier.urihttps://oarep.usim.edu.my/handle/123456789/10618
dc.identifier.volume13
dc.language.isoen_USen_US
dc.publisherFrontiersen_US
dc.relation.ispartofFrontiers in Aging Neuroscienceen_US
dc.subjectcarotid artery, ultrasound image, machine learning, deep learning, strokeen_US
dc.titlePerformance Analysis of Machine Learning and Deep Learning Architectures on Early Stroke Detection Using Carotid Artery Ultrasound Imagesen_US
dc.typeArticleen_US
dspace.entity.typePublication

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