An efficient data mining framework for the characterization of symptomatic and asymptomatic carotid plaque using bidimensional empirical mode decomposition technique.
Atherosclerosis is a type of cardiovascular disease which may cause stroke. It is due to the deposition of fatty plaque in the artery walls resulting in the reduction of elasticity gradually and hence restricting the blood flow to the heart. Hence, an early prediction of carotid plaque deposition is...
| Publicado en: | Medical & Biological Engineering & Computing Vol. 56; no. 9; pp. 1579 - 1594 |
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| Autores principales: | , , , , |
| Formato: | Journal Article |
| Publicado: |
Springer Nature
Sep2018
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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=131278129&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 131278129 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 01400118 PO0 jtl: Medical & Biological Engineering & Computing issn: 01400118 maglogo: N pubinfo: dt: Sep2018 vid: 56 iid: 9 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 131278129 131278129 NLM29473126 10.1007/s11517-018-1792-5 NLM29473126 131278129 ppf: 1579 ppct: 15 formats: fmt: – @attributes: type: T – @attributes: type: P tig: atl: An efficient data mining framework for the characterization of symptomatic and asymptomatic carotid plaque using bidimensional empirical mode decomposition technique. aug: au: Molinari, Filippo Raghavendra, U. Gudigar, Anjan Meiburger, Kristen M. Rajendra Acharya, U. affil: Department of Electronics and Telecommunications, Politecnico di Torino, Turin, Italy sug: subj: Atherosclerosis Pathology Data Mining Carotid Arteries Pathology Algorithms Ultrasonics Carotid Arteries ROC Curve Physics Atherosclerosis Scales ab: Atherosclerosis is a type of cardiovascular disease which may cause stroke. It is due to the deposition of fatty plaque in the artery walls resulting in the reduction of elasticity gradually and hence restricting the blood flow to the heart. Hence, an early prediction of carotid plaque deposition is important, as it can save lives. This paper proposes a novel data mining framework for the assessment of atherosclerosis in its early stage using ultrasound images. In this work, we are using 1353 symptomatic and 420 asymptomatic carotid plaque ultrasound images. Our proposed method classifies the symptomatic and asymptomatic carotid plaques using bidimensional empirical mode decomposition (BEMD) and entropy features. The unbalanced data samples are compensated using adaptive synthetic sampling (ADASYN), and the developed method yielded a promising accuracy of 91.43%, sensitivity of 97.26%, and specificity of 83.22% using fourteen features. Hence, the proposed method can be used as an assisting tool during the regular screening of carotid arteries in hospitals. Graphical abstract Outline for our efficient data mining framework for the characterization of symptomatic and asymptomatic carotid plaques. pubtype: Academic Journal doctype: Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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