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 Mehta, Pankaj; Desai, Amruta; Dutta, Shuvo; Sanjaya, P.R.; Asha, M.S.; Aravindan, M. Title A name given to the resource Redefining Disease Detection: Innovative Machine Learning and Wearable Sensor Integration 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 10th International Conference on Science Technology, Engineering and Mathematics, ICONSTEM 2025; Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1109/ICONSTEM65670.2025.11374892" target="_blank" rel="noreferrer noopener">https://doi.org/10.1109/ICONSTEM65670.2025.11374892</a> <br /><br /><a href="https://www.scopus.com/pages/publications/105034480441?origin=resultslist" target="_blank" rel="noreferrer noopener">https://www.scopus.com/pages/publications/105034480441?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 Mehta P., University Institute of Biotechnology, Department of Biosciences, Chandigarh University, Panjab, India; Desai A., School of Sciences, Pimpri Chinchwad University, Pune, India; Dutta S., Western Michigan University, Department of Physics, Kalamazoo, MI, United States; Sanjaya P.R., College of Dentistry, University of Hail, Department of Basic Dental &amp; Medical Sciences, Hail province, Saudi Arabia; Asha M.S., Christ(Deemed to Be University), Bengalure, India; Aravindan M., Agni College of Technology, Department of Electrical and Electronics Engineering, Chennai, Thazhambur, India Description An account of the resource Wearable sensor technology is considered to be one of the fastest growing fields of information and communication technologies and it has revolutionized the healthcare delivery by enabling continuous and real-time physiological monitoring. This research presents a novel approach that allows an early onset disease detection instigated with the prowess of advanced Graph Neural Network (GNNs) matched with the body streams gathered from wearable machines using its implementation technology - Pythonline of programming named Awesome Geometric libraries referred to as Aztec PyTorch. Graph neural networks (GNNs) are especially suitable within the scope of modeling complex relationships among multivariate inputs of the sensors for modeling the temporal and spatial subjacent dependence of the physiological signs with regards to reality. The proposed system analyzes the data acquired from the various wearable sensors such as heart rate, accelerometers and bio sensors, which help in anomaly detection and hence the detection of the patient having cardiovascular, metabolic and neurological diseases. The synergy between innovative deep learning models and sensors as ubiquitous technologies offers great promise to transform the provision of personalised healthcare services and dealing with disease in its early stages. 2025 IEEE. Subject The topic of the resource Disease Detection; Graph Neural Networks (GNNs); Personalized Healthcare; Predictive Analytics; PyTorch Geometric; Wearable Sensors Publisher An entity responsible for making the resource available Institute of Electrical and Electronics Engineers Inc. Relation A related resource ISBN: 979-833156187-1; 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