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 Sai, Vemula Harshith; John, Carolyn; Albin, S.; Nagaraju, Shamanth; Elappila, Manu; Athulya, S. Title A name given to the resource AI-Based Medical Assistance forProactive Healthcare Predictions andServices 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;1277 LNNS;pp.173-188 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1007/978-981-96-2700-4_14" target="_blank" rel="noreferrer noopener">https://doi.org/10.1007/978-981-96-2700-4_14</a> <br /><br /><a href="https://www.scopus.com/pages/publications/105011256760?origin=resultslist" target="_blank" rel="noreferrer noopener">https://www.scopus.com/pages/publications/105011256760?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 Sai V.H., Department of Computer Science and Engineering, CHRIST (Deemed to be University), Karnataka, Bengaluru, India; John C., Department of Computer Science and Engineering, CHRIST (Deemed to be University), Karnataka, Bengaluru, India; Albin S., Department of Computer Science and Engineering, CHRIST (Deemed to be University), Karnataka, Bengaluru, India; Nagaraju S., Department of Computer Science and Engineering, CHRIST (Deemed to be University), Karnataka, Bengaluru, India; Elappila M., Department of Computer Science and Engineering, CHRIST (Deemed to be University), Karnataka, Bengaluru, India; Athulya S., Department of Computer Science and Engineering, CHRIST (Deemed to be University), Karnataka, Bengaluru, India Description An account of the resource Healthcare systems must adapt to the requirements of the digital era. The proposed healthcare Artificial Intelligence (AI) assistance provides a safe and user-friendly platform for physicians, patients, and administrators to meet their specific needs. The systems architecture prioritizes user authentication and role-based access control to ensure that only authorized users have access to certain features. The technology allows patients to input their symptoms, which is the platforms cornerstone offering. The technology uses a Machine Learning (ML) model and a large medical database to properly forecast probable illnesses based on the symptoms presented. This predictive feature helps individuals make educated decisions about their health and seek medical assistance proactively. The systems creative approach extends to online consultations. Patients may seek consultations, schedule appointments, and conduct secure video chats from the comfort of their homes. This online consultation service offers a convenient and flexible option for medical treatment, especially for people with restricted mobility or wanting immediate assistance. This paper evaluates disease prediction using parameters like accuracy and confusion matrix performance. The neural network model performs better for the above parameters in comparison to the random forest and K-nearest neighbor ML models. The proposed system uses ML technology to deliver fast, accurate, and secure medical services, breaking down traditional healthcare barriers. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025. Subject The topic of the resource AI; Chatbot; Confusion Matrix; Django; ML; Neural network Publisher An entity responsible for making the resource available Springer Science and Business Media Deutschland GmbH Relation A related resource ISSN: 23673370; ISBN: 978-981962699-1; 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