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 Zaidi, Sidra; Paliwal, Nandini; Baby, Riya; Siby, Amala Title A name given to the resource Smart Healthcare Systems and Artificial Intelligence: Leveraging Data-Driven Solutions in Healthcare Date A point or period of time associated with an event in the lifecycle of the resource 01-01-2026 Source A related resource from which the described resource is derived Lecture Notes in Networks and Systems;Volume;1465 LNNS;pp.321-330 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1007/978-981-96-7517-3_27" target="_blank" rel="noreferrer noopener">https://doi.org/10.1007/978-981-96-7517-3_27</a> <br /><br /><a href="https://www.scopus.com/pages/publications/105020237048?origin=resultslist" target="_blank" rel="noreferrer noopener">https://www.scopus.com/pages/publications/105020237048?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 Zaidi S., School of Sciences, Christ University, Bengaluru, India; Paliwal N., School of Sciences, Christ University, Bengaluru, India; Baby R., School of Sciences, Christ University, Bengaluru, India; Siby A., School of Commerce, Finance and Accountancy, Christ University, Bengaluru, India Description An account of the resource Smart healthcare systems, powered by artificial intelligence (AI), enables drastic shift in healthcare sector. The benefits of data-driven solutions anchored in advanced disease diagnosis, efficient administrative records management, and operational efficiency. AI algorithms, including machine learning and deep learning, enable real-time data analysis from diverse sources such as Internet of medical Things (IoMT), wearable devices, and medical imaging. This facilitates early disease detection, personalized treatment plans, and predictive analytics, leading to improved health outcomes. Additionally, AI-powered systems optimize resource management, reduce human error, and streamline administrative tasks. While challenges such as data privacy, integration complexities, and ethical concerns exist, the potential of smart healthcare systems to revolutionize healthcare delivery is undeniable. This study explores the role of AI in advancing smart healthcare, focusing on the integration of data-driven technologies to create a more efficient, accessible, and patient-centered healthcare ecosystem. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2026. Subject The topic of the resource Artificial intelligence; Cybersecurity; Diagnosis; Healthcare; IoMT Publisher An entity responsible for making the resource available Springer Science and Business Media Deutschland GmbH Relation A related resource ISSN: 23673370; ISBN: 978-981967516-6; 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