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 Article Faculty Publications -Articles 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 Vineetha, K.R.; Bhargavi, Kovvuri N.; Narasamba Vanguri, G.L.; Mahilraj, Jenifer; Kannan, V. Title A name given to the resource FEATURE SELECTION AND CLASSIFICATION OF LEUKEMIC CELLS USING IOT AND 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 Journal of Mechanics of Continua and Mathematical Sciences;Volume;20;Issue;3;pp.36-53 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.26782/jmcms.2025.03.00004" target="_blank" rel="noreferrer noopener">https://doi.org/10.26782/jmcms.2025.03.00004</a> <br /><br /><a href="https://www.scopus.com/pages/publications/105000512011?origin=resultslist" target="_blank" rel="noreferrer noopener">https://www.scopus.com/pages/publications/105000512011?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 Vineetha K.R., Department of Computer Science, Christ University, Karnataka, Bengaluru, 560029, India; Bhargavi K.N., Department of Information Technology, Aditya College of Engineering and Technology, Surampalem, India; Narasamba Vanguri G.L., Department of Information Technology, Aditya College of Engineering and Technology, Surampalem, India; Mahilraj J., Department of AI &amp; DS, NPR College of Engineering and Technology, Dindigul, Natham, India; Kannan V., CLDC Research and Development, No.997, Mettupalayam Road, Near X-CutSignal, R.S.Puram, Tamil Nadu, Coimbatore, India Description An account of the resource Machine learning and the Internet of Things (IoT) have affected every step of the leukemia process, from diagnosis to understanding to therapy. Consequently, this study delves into the planning of an innovative system that employs IoT and machine learning techniques to precisely differentiate leukemic cells. Depending on the patient's samples, the system uses different ways to feature selection and cell classification. To pick the most informative collection of features that enables stable and accurate cell categorization into suitable categories, the offered research relies on strong machine-learning approaches for feature selection. Next, a classification model is used to classify cells based on their properties using the attributes that have been chosen. There is evidence that the suggested approach can classify leukemic cells with an identification rate of up to 99%, which is greater than the current methods. As a novel strategy for managing massive volumes of biological and medical samples, the suggested method will be an invaluable tool for doctors treating leukemia patients. The system's ability to process data from various Internet of Things (IoT) sources should aid its ability to learn and adapt to real-world clinical settings. With the results of this study in hand, we may be able to detect leukemia sooner, with greater precision, and maybe use more tailored treatments for each patient, leading to better results while reducing healthcare expenditures. 2025, Institute of Mechanics of Continua and Mathematical Sciences. All rights reserved. Subject The topic of the resource Diagnosing; Feature Selection; IoT; Leukemic Cells; Machine Learning; Understanding Publisher An entity responsible for making the resource available Institute of Mechanics of Continua and Mathematical Sciences Relation A related resource ISSN: 9738975; Language A language of the resource English Type The nature or genre of the resource Article Rights Information about rights held in and over the resource All Open Access; Gold Open Access Format The file format, physical medium, or dimensions of the resource online