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 Faculty Publications Conference Paper Faculty Publications- Conference Papers 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/. Creator An entity primarily responsible for making the resource Nagashruthi, M.K.; Hemanth, K.S. Title A name given to the resource Integrating Diverse Approaches in Medical Image Analysis: PAA-CNN and Feature Extraction Fusion for Classiation of Psychological Disorders using Anatomical Scans Date A point or period of time associated with an event in the lifecycle of the resource 01-01-2025 Source A related resource from which the described resource is derived Procedia Computer Science;Volume;260;pp.40-47 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1016/j.procs.2025.03.175" target="_blank" rel="noreferrer noopener">https://doi.org/10.1016/j.procs.2025.03.175</a> <br /><br /><a href="https://www.scopus.com/pages/publications/105008868634?origin=resultslist" target="_blank" rel="noreferrer noopener">https://www.scopus.com/pages/publications/105008868634?origin=resultslist</a> Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Nagashruthi M.K., School Of Computer Science and Applications, REVA University, Bengaluru, 560064, India; Hemanth K.S., Department of Computer Science, Christ University, Bengaluru, 560073, India Description An account of the resource A psychological disorder is a condition that impacts a persons behavior. Due to the contemporary way of life, a large number of individuals suffer from disorders like stress, depression, and other similar ones. These might turn into severe issues that would signiantly impact a persons quality of life. We present a sample framework that uses an Anatomical scan captured along with fMRI. Anatomical scans were used to extract characteristics, which were then utilized to classify using a random forest classir. In a follow-up experiment, CNN is applied to features obtained from the piecewise aggregate approximation method for multi-class classiation of psychological disorders. This method performs noticeably better than the conventional feature extraction techniques, and with this approach, obtained an accuracy of up to 79%. Combining several approaches may boost the classiation and prediction accuracy of medical data. 2025 The Authors. Published by Elsevier B.V. Subject The topic of the resource anatomical images; feature extraction; machine learning; peicewise aggregate approximation; prominent volumes Publisher An entity responsible for making the resource available Elsevier B.V. Relation A related resource ISSN: 18770509; Language A language of the resource English Type The nature or genre of the resource Conference paper Rights Information about rights held in and over the resource All Open Access; Gold Open Access Format The file format, physical medium, or dimensions of the resource online