Artificial Intelligence in Brain Disorders: Innovations in Diagnosis and Treatment

· · ·
· Academic Press
Ebook
400
Pages
Eligible

About this ebook

Artificial Intelligence in Brain Disorders: Innovations in Diagnosis and Treatment focuses on the utilization of AI and machine learning to enhance current practices in the diagnosis and treatment of neurological disorders. Each chapter provides in-depth exploration of specific areas where AI can improve existing methodologies, offering practical guidance, case studies, and research findings that can be directly applied in the field. It explains the application of AI in diagnosing and treating major neurological illnesses and showcases the potential of AI in predicting diseases such as epilepsy and neurodegenerative disorders.As such, this book offers a detailed overview of AI and machine learning techniques relevant to neurological research. - Offers a comprehensive exploration of cutting-edge AI, big data analytics, and machine learning methodologies specifically applied in the field of neurology - Presents various machine learning techniques such as image segmentation, classification, neural networks, and image processing - Showcases techniques in diagnosing early neurological disease identification and deep learning applications using advanced brain imaging technologies like EEG, MEG, fMRI, fNIRS, and PET - Provides practical insights and case studies
Artificial Intelligence in Brain Disorders: Innovations in Diagnosis and Treatment focuses on the utilization of AI and machine learning to enhance current practices in the diagnosis and treatment of neurological disorders. Each chapter provides in-depth exploration of specific areas where AI can...

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About the author

Pranav Kumar Prabhakar is Professor and Head of the Department of Biotechnology, School of Engineering and Technology, Nagaland University, Kohima, India. His research focuses on understanding molecular mechanisms involved in metabolic disorders, particularly diabetes, and on developing strategies for oral insulin delivery using natural products and biotechnology-based approaches. He is actively involved in research, academic mentoring, peer review, and editorial activities within the biomedical and biotechnology fields. His professional interests include translational research, signaling pathways associated with metabolic diseases, and the application of biotechnology to improve therapeutic outcomes. He contributes to scientific and academic initiatives that support advancements in biotechnology and healthcare research.

Arun Kumar Singh is Assistant Professor in the Department of Pharmacy at the University School of Pharmaceutical Sciences, Rayat Bahra University, Sahauran, India. His research interests include nano-formulation, cancer biology, and neuroscience, alongside digital and computational approaches such as machine learning, artificial intelligence, big data analytics, blockchain, and the Internet of Things. He has contributed academic books, book chapters, and review articles in pharmaceutical sciences and healthcare technology, with a focus on interdisciplinary approaches that integrate pharmaceutical research with emerging digital technologies.

Prateek Agrawal is professor and deputy dean at the School of Computer Science & Engineering, Lovely Professional University, Phagwara, Punjab, India. His research areas include natural language processing, computer vision, video processing, expert systems, deep learning applications, and other related topics. He is a senior member of IEEE and core member of IEEE India Council for Sustainable Development Activity, and is also a member of different reputed organizations like IET, MIR lab, and IAENG among others. Dr. Agarwal has published over 70 research papers in Scopus/SCIE indexed journals and conferences, 60 national patents, five edited books, and 10 book chapters. He is book series editor of the IOP series on next generation computing, and is a reviewer for many SCIE journals like Multimedia tools and Applications, Plos One, PeerJ, Oxford computer science, IEEE Access, and Ambient Intelligent & Humanized Computing.

Radu Prodan is professor of distributed systems at the Institute of Information Technology (ITEC), University of Klagenfurt, Austria. He was an associate professor at the University of Innsbruck until 2018. His research interests include performance, optimization, and resource management tools for parallel and distributed systems, as well as middleware system tools for cloud, fog, and edge computing. He has participated in numerous projects, including coordinating the Horizon 2020 project ARTICONF. He has coauthored over 200 publications and received three IEEE best paper awards. He is a member of ACM.

Pranav Kumar Prabhakar is Professor and Head of the Department of Biotechnology, School of Engineering and Technology, Nagaland University, Kohima, India. His research focuses on understanding molecular mechanisms involved in metabolic disorders, particularly diabetes, and on developing strategie...

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