Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Articles Article Faculty Publications -Articles Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Machine Learning Based Optimal Feature Selection for Pediatric Ultrasound Kidney Images Using Binary Coati Optimization Subject The topic of the resource Binary coati optimisation algorithm (BCOA); Chronic kidney disease (CKD); Feature selection (FS); Optimisation algorithm; Texture Description An account of the resource Chronic kidney disease (CKD) one of the most dangerous illnesses. Early detection is vital for improving survival rates and underscoring the need for an intelligent classifier to differentiate between normal and abnormal kidney ultrasound images. Features extracted from an image have a significant impact on classification accuracy. In this study, we present a Binary Coati optimization algorithm (BCOA) for feature selection in CKD, which focuses on reducing the high dimensionality features extracted from ultrasound images, including GLCM, GLRLM, GLSZM, GLDM, NGTDM, and first order, by employing BCOA-S shaped and BCOA-V shaped transfer functions that convert BCOA from a continuous search space to a binary form, which helps in the selection of optimal features to improve the classification performance while reducing the feature dimensionality. The reduced feature was evaluated using six machine-learning classifiers: Random Forest, Support Vector Machine, Decision tree, K-nearest Neighbor, XG-boost, and Nae Bayes. The efficiency of the proposed framework was assessed based on accuracy, precision, recall, specificity, f1 score and AUC curve. BCOA-V outperformed in terms of accuracy, precision, recall, specificity, F1 score and AUC curve by 99%,100%,97%,100%, 98%, and 98%, respectively. This makes it a superior choice for CKD diagnosis and is a valuable tool for feature selection in medical diagnosis. (2024), (Intelligent Network and Systems Society). All rights reserved. Creator An entity primarily responsible for making the resource Kausar F.; Ramamurthy B. Source A related resource from which the described resource is derived International Journal of Intelligent Engineering and Systems, Vol-17, No. 6, pp. 1300-1313. Publisher An entity responsible for making the resource available Intelligent Network and Systems Society Date A point or period of time associated with an event in the lifecycle of the resource 2024-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.22266/ijies2024.1231.94" target="_blank" rel="noreferrer noopener">https://doi.org/10.22266/ijies2024.1231.94</a> <br /><br /><a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85208113146&amp;doi=10.22266%2Fijies2024.1231.94&amp;partnerID=40&amp;md5=fe7d1e209b17077c8524f1e946ee92f0" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85208113146&amp;doi=10.22266%2fijies2024.1231.94&amp;partnerID=40&amp;md5=fe7d1e209b17077c8524f1e946ee92f0</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISSN: 2185310X Format The file format, physical medium, or dimensions of the resource Online Language A language of the resource English Type The nature or genre of the resource Article Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Kausar F., Department of Computer Science, CHRIST (Deemed to be University), Bangalore, 560029, India; Ramamurthy B., Department of Computer Science, CHRIST (Deemed to be University), Bangalore, 560029, India