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Cardiac Image-Based Heart Disease Diagnosis Using Bio-Inspired Optimized Technique for Feature Selection to Enhance Classification Accuracy
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Author(s): Manaswini Pradhan (Fakir Mohan University, India)
Copyright: 2023
Pages: 16
Source title:
Machine Learning and AI Techniques in Interactive Medical Image Analysis
Source Author(s)/Editor(s): Lipismita Panigrahi (GITAM University (Deemed), India), Sandeep Biswal (O.P. Jindal University, India), Akash Kumar Bhoi (KIET Group of Institutions, India & Sikkim Manipal University, India), Akhtar Kalam (Victoria University, Australia)and Paolo Barsocchi (Institute of Information Science and Technologies, Italy)
DOI: 10.4018/978-1-6684-4671-3.ch009
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Abstract
In this chapter, chimp optimization algorithm (ChOA) a bio-inspired optimized technique are proposed for selection of features to increase the classification accuracy of heart disease diagnosis. In this approach, noises contained in the cardiac image are removed using median filter initially. Then, GLCM features are extracted from the cardiac image. Among the extracted features, optimal features are chosen using ChOA algorithm. These selected features are taken as input to the classifier. In this approach, support vector neural network (SVNN) is used as a classifier. The classifier classifies the image into normal and abnormal. Simulation results depict that the ChOA-based SVNN performs better than the conventional SVNN, ANN, KNN, and SVM in terms of accuracy.
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