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 Book Chapter Faculty Publications- Book Chapter 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 Jenefa, J.; Athulya, R.; Varghese, Aaron John; Vetriveeran, Divya; Sambandam, Rakoth Kandan Title A name given to the resource CNN-based approach for brain tumor detection and severity prediction 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 Future Innovations in the Convergence of AI and Internet of Things in Medicine;pp.111-129 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.4018/979-8-3693-7703-1.ch006" target="_blank" rel="noreferrer noopener">https://doi.org/10.4018/979-8-3693-7703-1.ch006</a> <br /><br /><a href="https://www.scopus.com/pages/publications/85217642333?origin=resultslist" target="_blank" rel="noreferrer noopener">https://www.scopus.com/pages/publications/85217642333?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 Jenefa J., Christ University, India; Athulya R., Deloitte Parks Vista, India; Varghese A.J., Sabre Travel Technologies, India; Vetriveeran D., Christ University, India; Sambandam R.K., Christ University, India Description An account of the resource Artificial intelligence is widely used in healthcare, especially in medical imaging. It leads to advanced diagnosis using innovative approaches to analyze complex data more accurately and provide personalized treatments. This helps the clinicians efficiently analyze the imaging data, leading to early detection of diseases like brain tumors, cancer, cardiovascular diseases, etc. The research work focuses on the detection and severity prediction of brain tumors. Magnetic resonance imaging (MRI) scan images are preprocessed in the proposed model using different methods. The convolutional neural network model (CNN) is used to detect and predict brain tumors and can be used in personalized treatments. The proposed method has an accuracy of about 98% in classification and severity prediction. 2025, IGI Global Scientific Publishing. All rights reserved. Publisher An entity responsible for making the resource available IGI Global Relation A related resource ISBN: 979-836937705-5; 979-836937703-1; Language A language of the resource English Type The nature or genre of the resource Book chapter 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