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Please use this identifier to cite or link to this item: https://dspace.iiti.ac.in/handle/123456789/19363
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dc.contributor.authorTanveer, M.en_US
dc.date.accessioned2026-10-15T11:52:26Z-
dc.date.available2026-10-15T11:52:26Z-
dc.date.issued2026-
dc.identifier.citationGoel, T., Tanveer, M., Hussain, A., & Hussain, Z. (2026). DEEP LEARNING ASSESSMENT OF NEUROLOGICAL IMAGING (p. 224). Elsevier. https://doi.org/10.1016/C2024-0-00066-5en_US
dc.identifier.isbn978-044330291-6-
dc.identifier.otherEID(2-s2.0-105051985193)-
dc.identifier.urihttps://dx.doi.org/10.1016/C2024-0-00066-5-
dc.identifier.urihttps://dspace.iiti.ac.in/handle/123456789/19363-
dc.description.abstractDeep Learning Assessment of Neurological Imaging provides an introduction to deep learning structures and pre-processing methods for detecting MRI anomalies. The book also provides a comprehensive accounting of deep learning research on MRI images for Alzheimer's disease, Parkinson's disease, and schizophrenia, and includes a discussion on current research issues and future objectives. This book is a valuable resource to guide new entrants in the field, helping them make a meaningful impact in their development efforts. The book concludes with a brief overview of problems and potential future advancements in the field. Copyright © 2026 Elsevier Inc. All rights are reserved, including those for text and data mining, AI training, and similar technologies.en_US
dc.language.isoenen_US
dc.publisherElsevieren_US
dc.sourceDeep Learning Assessment of Neurological Imagingen_US
dc.titleDEEP LEARNING ASSESSMENT OF NEUROLOGICAL IMAGINGen_US
dc.typeBooken_US
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