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 Book Chapter 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/. Title A name given to the resource Detection of Alzheimers Disease Stages Based on Deep Learning Architectures from MRI Images Description An account of the resource Acquiring, utilizing and storing information of any sort is known as memory. The power of memory makes the life of mankind to be more alive and reasonable. Thus, the loss of one such great capability is a rather painful phase of human life which can be destructed by multiple reasons such as diseases and disorders. One such disease is Alzheimers disease (AD). Alzheimers disease progressively damages brain cells and degrades mental activity that leads to mental illness. The accurate diagnosis of AD at earlier stages will help to prevent the disease before the brain gets damaged completely. In analyzing neurodegenerative disorders, neuroimaging plays an important role in diagnosing subjects with AD, mild cognitive impairment (MCI), and cognitively normal (CN). In this study, advanced deep learning (DL) architectures with brain imaging techniques were employed to maximize the diagnostic accuracy of the model developed. The proposed method works with convolutional neural networks (CNNs) to analyze the MRI input-output modalities. The method is evaluated using Alzheimers Disease Neuroimaging Initiative (ADNI) dataset. Binary classification is done on AD and MCI subjects from CN. This method is efficient to analyze multiple classes with a less amount of training data. 2023 selection and editorial matter, Jyotismita Chaki; individual chapters, the contributors. Creator An entity primarily responsible for making the resource Antony F.; Anita H.B.; George J.A. Source A related resource from which the described resource is derived Diagnosis of Neurological Disorders Based on Deep Learning Techniques, pp. 47-60. Publisher An entity responsible for making the resource available CRC Press Date A point or period of time associated with an event in the lifecycle of the resource 2023-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1201/9781003315452-4" target="_blank" rel="noreferrer noopener">https://doi.org/10.1201/9781003315452-4</a> <br /><br /><a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85159478306&amp;doi=10.1201%2F9781003315452-4&amp;partnerID=40&amp;md5=bfc65e84d8ea15d2ab36c399533ccb48" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85159478306&amp;doi=10.1201%2f9781003315452-4&amp;partnerID=40&amp;md5=bfc65e84d8ea15d2ab36c399533ccb48</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISBN: 978-100087217-0; 978-103232524-8 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 Book chapter Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Antony F., Department of Computer Science, Christ (Deemed to be University), Bangalore, India; Anita H.B., Department of Computer Science, Christ (Deemed to be University), Bangalore, India; George J.A., Department of Computer Science, Christ (Deemed to be University), Bangalore, India