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 Avhad, Priyanka Ravindra; Radhakrishnan, G.V.; Parashar, Jyoti; Malik, Khusbhoo; Gupta, Komal; Upreti, Kamal Title A name given to the resource Patient Digital Twins for Dynamic Hospital Supply Chain Management AI-Based Predictive Resource Allocation 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 Proceedings of International Conference on Digital Innovations for Sustainable Solutions, ICDISS 2025; Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1109/ICDISS68238.2025.11320584" target="_blank" rel="noreferrer noopener">https://doi.org/10.1109/ICDISS68238.2025.11320584</a> <br /><br /><a href="https://www.scopus.com/pages/publications/105033566276?origin=resultslist" target="_blank" rel="noreferrer noopener">https://www.scopus.com/pages/publications/105033566276?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 Avhad P.R., Dept. of Computer Science&amp; Engineering, Veermata Jijabai Technological Institute, Mumbai, India; Radhakrishnan G.V., Department of Economics &amp; Finance, Kalinga School of Management KIIT, Bhubaneswar, India; Parashar J., Department of Computer Applications, Panipat Institute of Engineering &amp; Technology College, Haryana, Panipat, India; Malik K., School of Law, Christ University Delhi NCR, Ghaziabad, India; Gupta K., Accenture, Bangalore, India; Upreti K., Department of Computer Science, Christ University Delhi NCR, Ghaziabad, India Description An account of the resource The fusion of Digital Twin (DT) technology and Artificial Intelligence (AI) holds great promise for the optimization of hospital supply chain management and resource allocation. This paper proposes a patient-specific digital twin framework aimed at forecasting hospital staffing needs and aiding supply planning by means of AI-based analytics. Preprocessing and modeling of hospital records that included admission information, medical procedures, room types, usage of supplies, and patterns of staffing were achieved by utilizing advanced machine learning algorithms. The strategy illustrated better performance compared to baseline strategies and had interpretability from feature importance analysis, which emphasized length of stay, critical care admissions, and specialized procedures as influential drivers of staffing requirements. The results show that the patient digital twin can optimize operational efficiency, avoid supply deficits, and facilitate evidence-based decisions. The suggested framework is consistent with the vision of contemporary healthcare supply chains in that it promotes resilience, flexibility, and smart resource management. 2025 IEEE. Subject The topic of the resource Artificial Intelligence; Digital Twin; Hospital Supply Chain; Predictive Analytics; SHAP Interpretability; Staffing Optimization Publisher An entity responsible for making the resource available Institute of Electrical and Electronics Engineers Inc. Relation A related resource ISBN: 979-833155641-9; 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