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 Shradha, V. Sai; Prathap, Boppuru Rudra Title A name given to the resource Artificial Intelligence-Driven Perspectives on Maternal Health: Revealing Important Aspects and Improving Pregnancy Results via Machine Learning 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 Lecture Notes in Networks and Systems;Volume;1354 LNNS;pp.227-243 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1007/978-981-96-4880-1_18" target="_blank" rel="noreferrer noopener">https://doi.org/10.1007/978-981-96-4880-1_18</a> <br /><br /><a href="https://www.scopus.com/pages/publications/105019292392?origin=resultslist" target="_blank" rel="noreferrer noopener">https://www.scopus.com/pages/publications/105019292392?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 Shradha V.S., Computer Science and Engineering, Christ University, Bangalore, India; Prathap B.R., Department of Computer Science and Engineering, M S Ramaiah University of Applied Sciences, Bangalore, India Description An account of the resource A number of factors, including genetic, environmental and social ones, affect the intricate biological process of pregnancy. The developing foetuss health as well as the mothers must be maintained in the necessary secure equilibrium of these variables. The mothers health, which encompasses her mental as well as physical health, lifestyle decisions, money, social support systems and educational attainment, will determine whether the pregnancy ends well. Medical research has changed as a result of the long-awaited tools for processing for complicated datasets that have been made possible by recent advancements in machine learning models. These models have the ability to identify correlations between characteristics that are difficult for traditional analytical techniques to uncover. Therefore, scientists can improve their understanding of the elements influencing conception and create diagnostic tools by utilizing machine learning technology for timely intervention and customized treatment. Machine learning encompasses various techniques, such as logistic regression, linear regression, random forest, K-Nearest Neighbours and gradient boosting classifier. While Random Forest is an effective way to handle big databases with multiple dimensions and interactions, KNN classifiers are excellent for more organic, data-driven cluster finding of relevant instances and association investigation between various parameters and pregnancy outcomes. Logistic regression only explains the ways in which individual factors affect pregnancy outcomes; it cannot handle binary outcomes as well as linear regression does. We will look for significant determinants of pregnancy outcomes and assess each models performance. Important elements will also be expanded upon. Pregnant patients care, professional practice and improved program decisions may all benefit from this information. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025. Subject The topic of the resource Healthcare interventions; Machine learning; Maternal health; Predictive modelling; Pregnancy outcomes Publisher An entity responsible for making the resource available Springer Science and Business Media Deutschland GmbH Relation A related resource ISSN: 23673370; ISBN: 978-981964879-5; 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