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 An efficient deep learning approach for identifying interstitial lung diseases using HRCT images Subject The topic of the resource deep learning; DL; high-resolution computed tomography; HRCT; ILD; interstitial lung disease; multi-label classification; transfer learning Description An account of the resource Interstitial lung disease (ILD) encompasses over 200 fatal lung disorders affecting the interstitium, leading to significant mortality rates. We propose an AI-driven approach to diagnose and classify ILD from high-resolution computed tomography (HRCT) images. The research utilises a dataset of 3,045 HRCT images and employs a two-tier ensemble method that combines various machine learning (ML) models, convolutional neural networks (CNNs), and transfer learning. Initially, ML models achieve high accuracy, with the J48 model at 93.08% accuracy, mainly highlighting the importance of diagonal-wise standard deviation. Deep learning techniques are then applied, with three CNN models achieving test accuracies of 94.08%, 92.04%, and 93.72%. Transfer learning models also show promise, with InceptionV3 at 92.48% accuracy. Ensembling these models further boosts accuracy, with the ensemble of three CNN models reaching 97.42%. This research has the potential to advance ILD diagnosis, offering a robust computational framework that enhances accuracy and ultimately improves patient outcomes. Copyright 2024 Inderscience Enterprises Ltd. Creator An entity primarily responsible for making the resource Raju N.; Augustine D.P. Source A related resource from which the described resource is derived International Journal of Computational Science and Engineering, Vol-27, No. 3, pp. 286-301. Publisher An entity responsible for making the resource available Inderscience Publishers 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/10.1504/IJCSE.2024.138427" target="_blank" rel="noreferrer noopener">https://doi.org/10.1504/IJCSE.2024.138427</a> <br /><br /><a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85192870037&amp;doi=10.1504%2FIJCSE.2024.138427&amp;partnerID=40&amp;md5=b3c6ded0e2833e6e04cba94656d8187a" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85192870037&amp;doi=10.1504%2fIJCSE.2024.138427&amp;partnerID=40&amp;md5=b3c6ded0e2833e6e04cba94656d8187a</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISSN: 17427185 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 Raju N., Department of Computer Science, CHRIST (Deemed to be University), Bangalore, India; Augustine D.P., Department of Computer Science, CHRIST (Deemed to be University), Bangalore, India