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 John Joshua, H.; Prathish, R.K.; Vasanth, U.; Jaya Priya, J.; Vinay, M.; Deepa, S. Title A name given to the resource Statistical Learning inPharmacovigilance: A Data-Driven Approach to AI-Enhanced Drug Safety Monitoring 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;1612 LNNS;pp.155-166 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1007/978-981-95-2872-1_12" target="_blank" rel="noreferrer noopener">https://doi.org/10.1007/978-981-95-2872-1_12</a> <br /><br /><a href="https://www.scopus.com/pages/publications/105028291638?origin=resultslist" target="_blank" rel="noreferrer noopener">https://www.scopus.com/pages/publications/105028291638?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 John Joshua H., Department of Computer Science, Christ (Deemed to be University), Karnataka, Bengaluru, India; Prathish R.K., Department of Computer Science, Christ (Deemed to be University), Karnataka, Bengaluru, India; Vasanth U., Department of Computer Science, Christ (Deemed to be University), Karnataka, Bengaluru, India; Jaya Priya J., Department of Computer Science, Christ (Deemed to be University), Karnataka, Bengaluru, India; Vinay M., Department of Computer Science, Christ (Deemed to be University), Karnataka, Bengaluru, India; Deepa S., Department of Computer Science, Christ (Deemed to be University), Karnataka, Bengaluru, India Description An account of the resource Pharmacovigilance is transforming at warp speed in response to big data and advanced analytical techniques. This paper will provide an overview of where pharmacovigilance currently stands by focusing on integrating artificial intelligence (AI), machine learning (ML) and real-world data (RWD) in order to improve drug safety monitoring. These new methods are increasingly supplementing traditional ones which serve as their base. The purpose of this survey is to assess how effective they are, point out the major challenges standing in their way as well as offer recommendations for future research. In conclusion, although AI and ML could prove helpful especially with handling large volume and complexity of datasets, there is a need for tackling data quality, integration issues and regulatory acceptance concerns first. Standardized methodologies should be worked out and collaboration among all stakeholders encouraged so as to maximize the pharmacovigilance benefits that can come from these technologies. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2026. Subject The topic of the resource Adverse drug reactions (ADRs); Data mining; Pharmacovigilance; Real-world data (RWD) Publisher An entity responsible for making the resource available Springer Science and Business Media Deutschland GmbH Relation A related resource ISSN: 23673370; ISBN: 978-981952871-4; 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