Machine learning techniques as a helpful tool toward determination of plaque vulnerability

IEEE Transactions on Biomedical Engineering

Volumn 59, Issue 4, 2012, Pages 1155-1161

  Cilla, Myriam ^a,b   Martínez, Javier ^c   Pena, Estefanía ^a,b   Martínez, Miguel Ángel ^a,b  

^a UNIVERSITY OF ZARAGOZA   (Spain)

^b UNIVERSITAT AUTÒNOMA DE BARCELONA   (Spain)

^c CENTRO UNIVERSITARIO DE LA DEFENSA   (Spain)

Author keywords

Artificial neural network (ANN); coronary disease; parametric finite element analysis; support vector machine (SVM)

Indexed keywords

3D-FINITE ELEMENT ANALYSIS; ACUTE CORONARY SYNDROMES; CARDIO-VASCULAR DISEASE; COMPUTATION TIME; COMPUTATIONAL TECHNOLOGY; CORONARY ARTERY DISEASE; CORONARY DISEASE; CORONARY VESSEL; GEOMETRICAL FEATURES; MACHINE LEARNING TECHNIQUES; MAIN MEMORY; MAXIMUM PRINCIPAL STRESS; PARAMETRIC FINITE ELEMENT ANALYSIS; PLAQUE RUPTURE; POTENTIAL APPLICATIONS; SUDDEN DEATHS; SUPPORT VECTOR MACHINE (SVM); TISSUE PROPERTIES;

DISEASES; FINITE ELEMENT METHOD; LEARNING ALGORITHMS; NEURAL NETWORKS; STRESS CONCENTRATION; TISSUE;

SUPPORT VECTOR MACHINES;

LIPID;

ACUTE CORONARY SYNDROME; ARTERY; ARTERY COMPLIANCE; ARTICLE; ARTIFICIAL NEURAL NETWORK; ATHEROMA; ATHEROSCLEROSIS; ATHEROSCLEROTIC PLAQUE; BIOMECHANICS; BLOOD VESSEL; CLINICAL DECISION MAKING; CORONARY ARTERY; CORONARY ARTERY ATHEROSCLEROSIS; CORONARY ARTERY DISEASE; CORONARY ARTERY SURGERY; FINITE ELEMENT ANALYSIS; GEOMETRY; HUMAN; MACHINE LEARNING; MATHEMATICAL MODEL; MEDICAL TECHNOLOGY; PREDICTION; PREOPERATIVE EVALUATION; RISK ASSESSMENT; STRESS; SUPPORT VECTOR MACHINE; THREE DIMENSIONAL IMAGING; TISSUES; TREATMENT PLANNING;

ARTERIES; ARTIFICIAL INTELLIGENCE; ATHEROSCLEROSIS; BLOOD FLOW VELOCITY; COMPUTER SIMULATION; DIAGNOSIS, COMPUTER-ASSISTED; ECHOCARDIOGRAPHY; HUMANS; MODELS, CARDIOVASCULAR; PLAQUE, ATHEROSCLEROTIC;

EID: 84858962857     PISSN: 00189294     EISSN: 15582531     Source Type: Journal    
DOI: 10.1109/TBME.2012.2185495     Document Type: Article

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