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 Joseph, Raima; Goel, Nishtha; Shreenithi, Livia; Yogish, Deepa Title A name given to the resource JivaCare: A Smart Health Care Application Integrating Home Remedies for Holistic Well-Being 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 2025 International Conference on Computing for Sustainability and Intelligent Future, COMP-SIF 2025; Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1109/COMP-SIF65618.2025.10969972" target="_blank" rel="noreferrer noopener">https://doi.org/10.1109/COMP-SIF65618.2025.10969972</a> <br /><br /><a href="https://www.scopus.com/pages/publications/105004982732?origin=resultslist" target="_blank" rel="noreferrer noopener">https://www.scopus.com/pages/publications/105004982732?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 Joseph R., School of Engineering and Technology, Christ University, Department of Cse, Bengaluru, India; Goel N., School of Engineering and Technology, Christ University, Department of Cse, Bengaluru, India; Shreenithi L., School of Engineering and Technology, Christ University, Department of Cse, Bengaluru, India; Yogish D., School of Engineering and Technology, Christ University, Department of Cse, Bengaluru, India Description An account of the resource JivaCare is a smart health care application that aims to diagnose common illnesses and recommend home remedies by leveraging advancements in Artificial Intelligence (AI) and Machine Learning (ML). Initially, a custom dataset of diseases and symptoms was used to develop a disease-diagnoses chatbot. However, challenges such as limited accuracy and rigid disease-symptom mapping were identified. To address these, GPT-3.5 API was integrated via RapidAPI, enhancing conversational quality without requiring extensive training while improving response quality. A MySQL database was implemented to store conversational history and session-based memory. Subsequently, the focus transitioned to a text classification approach using a 5,634-sample dataset from HuggingFace. This enabled flexible symptom-to-disease classification, overcoming the limitations of the initial dataset. Five machine learning models were evaluated, with Logistic Regression achieving the highest accuracie of 85 % after fine-tuning its hyperparameters. Additionally, neural network architectures such as GRU, RNN and CNN were also employed, achieving validation accuracies of 76%, 82% and 84%, respectively. The results demonstrate the effectiveness of integrating ML and deep learning techniques for accurate disease prediction and remedy recommendation. This work can establish the foundation for a scalable and user-friendly healthcare system, bridging the gap between AI and personalised natural health benefits. 2025 IEEE. Subject The topic of the resource Healthcare; JivaCare; Logistic Regression; Text Classification Publisher An entity responsible for making the resource available Institute of Electrical and Electronics Engineers Inc. Relation A related resource ISBN: 979-833153853-8; 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