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 Sneha, Mishael; Gokulapriya, R.; Balamurugan, M. Title A name given to the resource Comprehensive Analysis of Canine Parvovirus Outbreaks: Predictive Modeling and Evaluation Metrics 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;5588 LNNS;pp.651-660 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1007/978-981-96-1918-4_46" target="_blank" rel="noreferrer noopener">https://doi.org/10.1007/978-981-96-1918-4_46</a> <br /><br /><a href="https://www.scopus.com/pages/publications/105010031265?origin=resultslist" target="_blank" rel="noreferrer noopener">https://www.scopus.com/pages/publications/105010031265?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 Sneha M., Department of Computer Science and Engineering, CHRIST (Deemed to be University), Bengaluru, India; Gokulapriya R., Department of Computer Science and Engineering, CHRIST (Deemed to be University), Bengaluru, India; Balamurugan M., Department of Computer Science and Engineering, CHRIST (Deemed to be University), Bengaluru, India Description An account of the resource This paper addresses the persistent threat of Canine Parvovirus (CPV) to canine health, exploring a spectrum of outcomes from recovery to fatalities. Employing a fusion of machine learning techniques and comprehensive evaluation metrics, we present a robust analysis of CPV outbreaks. Our methodology involves the development of a deep learning-based predictive model designed to anticipate CPV case outcomes based on symptoms and diverse contributing factors, with performance monitoring through visualization techniques. The study delves into the intricacies of a dataset featuring diverse features such as age, breed, symptoms, treatment, and geographic location. Through meticulous preprocessing and feature encoding, we establish a powerful deep learning model proficient in discerning intricate patterns within the data. Model evaluation encompasses key metrics, including accuracy, precision, recall, F1-score, confusion matrix, Cohens Kappa, and Matthews Correlation Coefficient, providing a comprehensive assessment of predictive capabilities. Our findings highlight the models proficiency in anticipating CPV outcomes, suggesting potential enhancements in decision-making within veterinary practice. Insights derived from this research contribute to the refinement of CPV diagnosis, treatment, and prevention strategies, ultimately benefiting the well-being of canine companions. The projects results demonstrate the efficacy of the proposed models in forecasting the prevalence and survival rate of the CPV virus in dogs using basic parameters. This approach eliminates the need for costly and time-consuming laboratory tests, typically requiring 1224h for results, showcasing a practical and efficient solution for CPV management. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025. Subject The topic of the resource Canine Parvovirus (CPV); Convolutional Neural Networks; Machine learning Publisher An entity responsible for making the resource available Springer Science and Business Media Deutschland GmbH Relation A related resource ISSN: 23673370; ISBN: 978-981961917-7; 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