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 Articles 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/. Title A name given to the resource Machine Learning Technique to Detect Radiations in the Brain Subject The topic of the resource Brain morphology; Electromagnetic field radiations; Image processing; Machine learning; Segmentation Description An account of the resource The brain of humans and other organisms is affected in various ways through the electromagnetic field (EMF) radiations generated by mobile phones and cell phone towers. Morphological variations in the brain are caused by the neurological changes due to the revelation of EMF. Cellular level analysis is used to measure and detect the effect of mobile radiations, but its utilization seems very expensive, and it is a tedious process, where its analysis requires the preparation of cell suspension. In this regard, this research article proposes optimal broadcasting learning to detect changes in brain morphology due to the revelation of EMF. Here, Drosophila melanogaster acts as a specimen under the revelation of EMF. Automatic segmentation is performed for the brain to attain the microscopic images from the prejudicial geometrical characteristics that are removed to detect the effect of revelation of EMF. The geometrical characteristics of the brain image of that is microscopic segmented are analyzed. Analysis results reveal the occurrence of several prejudicial characteristics that can be processed by machine learning techniques. The important prejudicial characteristics are given to four varieties of classifiers such as nae Bayes, artificial neural network, support vector machine, and unsystematic forest for the classification of open or nonopen microscopic image of D. melanogaster brain. The results are attained through various experimental evaluations, and the said classifiers perform well by achieving 96.44% using the prejudicial characteristics chosen by the feature selection method. The proposed system is an optimal approach that automatically identifies the effect of revelation of EMF with minimal time complexity, where the machine learning techniques produce an effective framework for image processing. This work is licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Creator An entity primarily responsible for making the resource Gothai E.; Baseera A.; Prabu P.; Venkatachalam K.; Saravanan K.; SathishKumar S. Source A related resource from which the described resource is derived Computer Systems Science and Engineering, Vol-42, No. 1, pp. 149-163. Publisher An entity responsible for making the resource available Tech Science Press Date A point or period of time associated with an event in the lifecycle of the resource 2022-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.32604/CSSE.2022.020619" target="_blank" rel="noreferrer noopener">https://doi.org/10.32604/CSSE.2022.020619</a> <br /><br /><a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85121609894&amp;doi=10.32604%2FCSSE.2022.020619&amp;partnerID=40&amp;md5=bf5b14750fa5d3b433c59a2534f30d31" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85121609894&amp;doi=10.32604%2fCSSE.2022.020619&amp;partnerID=40&amp;md5=bf5b14750fa5d3b433c59a2534f30d31</a> Rights Information about rights held in and over the resource All Open Access; Hybrid Gold Open Access Relation A related resource ISSN: 2676192; CODEN: CSSEE Format The file format, physical medium, or dimensions of the resource Online Language A language of the resource English Type The nature or genre of the resource Article Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Gothai E., Department of Computer Science and Engineering, Kongu Engineering College, Erode, 638060, India; Baseera A., School of Computing Science and Engineering, VIT Bhopal University, Bhopal, 466114, India; Prabu P., Department of Computer Science, CHRIST (Deemed to be University), Bangalore, 560029, India; Venkatachalam K., Department of Computer Science and Engineering, CHRIST (Deemed to be University), Bangalore, India; Saravanan K., Department of Computer Science and Engineering, Erode Sengunthar Engineering College, Thudupathi, 638057, India; SathishKumar S., Department of EEE, M.Kumarasamy College of Engineering, Tamilnadu, Karur, 639113, India