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 Pavithra, K.; Balakrishnan, R.; Loveline Zeema, J. Title A name given to the resource Next Generation AI-Enhanced Intelligent Imaging for Automated Knee X-ray Interpretation in Osteoarthritis: Front office Integration and Employee Training 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 2025 IEEE International Conference on Modern Electronics Devices and Intelligent Communication Systems, MEDCOM 2025;pp.456-461 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1109/MEDCOM67532.2025.11404948" target="_blank" rel="noreferrer noopener">https://doi.org/10.1109/MEDCOM67532.2025.11404948</a> <br /><br /><a href="https://www.scopus.com/pages/publications/105036727841?origin=resultslist" target="_blank" rel="noreferrer noopener">https://www.scopus.com/pages/publications/105036727841?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 Pavithra K., CHRIST (Deemed to Be University), Dept of Computer Science, Bangalore, India; Balakrishnan R., MS Ramaiah University of Applied Sciences, Dept of Hospitality Management, Bangalore, India; Loveline Zeema J., CHRIST (Deemed to Be University), Dept of Computer Science, Bangalore, India Description An account of the resource Osteoarthritis is a long-lasting musculoskeletal ailment in which the degenerative alterations in the cartilage of the articles progressively arise. As the pathological anatomy develops to bone structure degeneration, it results in pain, stiffness and functional impairment. It results in immobility, reduced quality of life, more susceptibility to fractures, hospitalization, and mental health problems in the older adults and postmenopausal women. To address the increasing global prevalence of OA and the necessity to diagnose X-rays of the knee promptly, affordably and accessibly, this paper presents an AI-based imaging system based on the use of Convolutional Neural Networks (CNNs) and compares their results with the existing machine learning models. The framework will be structured to integrate the front-office workflows and streamline the diagnostic process of patient registration to report delivery and establish a well-organized staff training ecosystem aimed at enabling clinical staff to operate the AI-enabled workflow and adapt to it. The study offers a comprehensive, deployment ready, diagnostic platform through advanced automation, user oriented front-office functionality and the consistent upskilling of the workforce, to provide scalable, precise, cost effective OA detection, clinical efficiency, interpretative variability reduction, and workforce transition to scalable intelligent, patient centred care. 2025 IEEE. Subject The topic of the resource Artificial Intelligence (AI) in Healthcare; Clinical Workflow Optimization; Employee Training in AI Systems; Front office Integration; Knee X-ray Interpretation; Osteoarthritis Diagnosis Publisher An entity responsible for making the resource available Institute of Electrical and Electronics Engineers Inc. Relation A related resource ISBN: 979-833157444-4; 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 Restricted Access; Hardcopy may be available in the library Format The file format, physical medium, or dimensions of the resource online