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Author: Indranath Chatterjee
Publisher: CRC Press
ISBN: 1040216293
Category : Medical
Languages : en
Pages : 273
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Book Description
Unveil the next frontier in neurodegenerative disorder research with Integrating Neuroimaging, Computational Neuroscience, and Artificial Intelligence. This groundbreaking book goes beyond traditional approaches, utilizing the power of interdisciplinary integration to illuminate new pathways in diagnosis and treatment. From AI-driven diagnostics to computational neuroscience models, this book showcases the forefront of innovation. Join us in exploring the future of neurodegenerative care, where collaboration and cutting-edge technology converge to redefine possibilities. Key Features: Integrates diverse fields of research, from neuroimaging to computational neuroscience and Artificial Intelligence. Emphasizes the translation of research findings into practical applications, ultimately benefitting patients and clinical practice. Reviews the implementation of Artificial Intelligence and computational models in diagnostic settings. Elucidates the current state of translational neuroscience exploring potential areas for further research and collaboration, including personalized treatments and drug development. Contributions from an international team of experts from diverse disciplines.
Author: Indranath Chatterjee
Publisher: CRC Press
ISBN: 1040216293
Category : Medical
Languages : en
Pages : 273
Get Book Here
Book Description
Unveil the next frontier in neurodegenerative disorder research with Integrating Neuroimaging, Computational Neuroscience, and Artificial Intelligence. This groundbreaking book goes beyond traditional approaches, utilizing the power of interdisciplinary integration to illuminate new pathways in diagnosis and treatment. From AI-driven diagnostics to computational neuroscience models, this book showcases the forefront of innovation. Join us in exploring the future of neurodegenerative care, where collaboration and cutting-edge technology converge to redefine possibilities. Key Features: Integrates diverse fields of research, from neuroimaging to computational neuroscience and Artificial Intelligence. Emphasizes the translation of research findings into practical applications, ultimately benefitting patients and clinical practice. Reviews the implementation of Artificial Intelligence and computational models in diagnostic settings. Elucidates the current state of translational neuroscience exploring potential areas for further research and collaboration, including personalized treatments and drug development. Contributions from an international team of experts from diverse disciplines.
Author: Rong Chen
Publisher: Frontiers Media SA
ISBN: 2889666832
Category : Science
Languages : en
Pages : 290
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Book Description
Author: Xi-Nian Zuo
Publisher:
ISBN:
Category :
Languages : en
Pages : 0
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Book Description
This eBook is a collection of articles from a Frontiers Research Topic. Frontiers Research Topics are very popular trademarks of the Frontiers Journals Series: they are collections of at least ten articles, all centered on a particular subject. With their unique mix of varied contributions from Original Research to Review Articles, Frontiers Research Topics unify the most influential researchers, the latest key findings and historical advances in a hot research area! Find out more on how to host your own Frontiers Research Topic or contribute to one as an author by contacting the Frontiers Editorial Office: frontiersin.org/about/contact.
Author: Thomas Trappenberg
Publisher: Oxford University Press (UK)
ISBN: 0199568413
Category : Mathematics
Languages : en
Pages : 417
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Book Description
The new edition of Fundamentals of Computational Neuroscience build on the success and strengths of the first edition. It introduces the theoretical foundations of neuroscience with a focus on the nature of information processing in the brain. The book covers the introduction and motivation of simplified models of neurons that are suitable for exploring information processing in large brain-like networks. Additionally, it introduces several fundamental networkarchitectures and discusses their relevance for information processing in the brain, giving some examples of models of higher-order cognitive functions to demonstrate the advanced insight that can begained with such studies.
Author: KHRITISH SWARGIARY
Publisher: ERA, US
ISBN:
Category : Education
Languages : en
Pages : 534
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Book Description
The fusion of Artificial Intelligence (AI) with psychology represents one of the most exciting and transformative developments in modern science. As AI technologies continue to advance, their potential to reshape the field of psychology is immense, offering novel ways to analyze, diagnose, and treat a variety of psychological conditions. The integration of AI into psychological practice, research, and education is already yielding promising results, enhancing our understanding of human behavior, and providing new tools for practitioners and researchers alike. Integrating Artificial Intelligence in Branches of Psychology: A Comprehensive Exploration is a work born from the growing need to understand the intersection of these two powerful fields. In this book, we explore the many ways in which AI is being utilized across the diverse branches of psychology, from clinical and cognitive psychology to health and social psychology. The goal is to present a holistic view of how AI is transforming psychological theory and practice, offering insights into the benefits, challenges, and ethical considerations that come with this technological advancement. This book is intended for both scholars and practitioners in the field of psychology, as well as those working in AI and related technologies who are interested in the applications of their work to the human sciences. Each Chapter is designed to delve into the specific areas of psychology where AI has made a notable impact, providing a comprehensive overview of both foundational concepts and cutting-edge innovations. Topics range from AI-driven behavioral interventions to neural network models that simulate cognitive processes, and from AI's role in educational technologies to its contributions to forensic psychology and criminal profiling. In each case, we examine not only the technical aspects of AI but also its psychological implications, ensuring that the reader gains a well-rounded understanding of these complex and interwoven domains. The integration of AI into psychology is still in its early stages, but it is clear that this synergy holds the promise of a more nuanced and effective approach to understanding and improving human behavior. As we continue to navigate this exciting frontier, it is crucial to consider both the opportunities and challenges that AI presents. This book provides a platform for engaging with these ideas, encouraging thoughtful reflection on the role of AI in shaping the future of psychology. I invite you, the reader, to embark on this journey through the intersections of AI and psychology, where each Chapter opens a window into new possibilities and insights. As we look toward the future, it is clear that the integration of AI will continue to play a central role in advancing our understanding of the mind and behavior. KHRITISH SWARGIARY (M.A. in PSYCHOLOGY, M.A. in EDUCATION, CE-IB: Constructivism in Education: Perspectives from International Baccalaureate, DPEA-GE: Disaster Prevention & Education in Asia: Geography Education Perspective, ME-SA: Mathematics Education: Student Agency - Problem Solving, Shape, Measurement & Pattern, MT-VII: Mathematical Thinking VII, EP-IBL: Educational Practices: Inquiry-Based Learning for 21st Century (IB Inspired), GPT-HS: Geographic Perspective & Thinking in Senior High School ,CT-PS: Computational Thinking: Development at Primary School from Center for Research on International Development, University of Tsukuba, Japan) Email:
[email protected]
Author: John Paul Kottcamp
Publisher: Wentworth Press
ISBN: 9781010916819
Category : History
Languages : en
Pages : 78
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Book Description
This work has been selected by scholars as being culturally important, and is part of the knowledge base of civilization as we know it. This work was reproduced from the original artifact, and remains as true to the original work as possible. Therefore, you will see the original copyright references, library stamps (as most of these works have been housed in our most important libraries around the world), and other notations in the work. This work is in the public domain in the United States of America, and possibly other nations. Within the United States, you may freely copy and distribute this work, as no entity (individual or corporate) has a copyright on the body of the work. As a reproduction of a historical artifact, this work may contain missing or blurred pages, poor pictures, errant marks, etc. Scholars believe, and we concur, that this work is important enough to be preserved, reproduced, and made generally available to the public. We appreciate your support of the preservation process, and thank you for being an important part of keeping this knowledge alive and relevant.
Author: Kenji Doya
Publisher: MIT Press
ISBN: 026204238X
Category : Bayesian statistical decision theory
Languages : en
Pages : 341
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Book Description
Experimental and theoretical neuroscientists use Bayesian approaches to analyze the brain mechanisms of perception, decision-making, and motor control.
Author: Daniel Durstewitz
Publisher: Springer
ISBN: 3319599763
Category : Medical
Languages : en
Pages : 308
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Book Description
This book is intended for use in advanced graduate courses in statistics / machine learning, as well as for all experimental neuroscientists seeking to understand statistical methods at a deeper level, and theoretical neuroscientists with a limited background in statistics. It reviews almost all areas of applied statistics, from basic statistical estimation and test theory, linear and nonlinear approaches for regression and classification, to model selection and methods for dimensionality reduction, density estimation and unsupervised clustering. Its focus, however, is linear and nonlinear time series analysis from a dynamical systems perspective, based on which it aims to convey an understanding also of the dynamical mechanisms that could have generated observed time series. Further, it integrates computational modeling of behavioral and neural dynamics with statistical estimation and hypothesis testing. This way computational models in neuroscience are not only explanatory frameworks, but become powerful, quantitative data-analytical tools in themselves that enable researchers to look beyond the data surface and unravel underlying mechanisms. Interactive examples of most methods are provided through a package of MatLab routines, encouraging a playful approach to the subject, and providing readers with a better feel for the practical aspects of the methods covered. "Computational neuroscience is essential for integrating and providing a basis for understanding the myriads of remarkable laboratory data on nervous system functions. Daniel Durstewitz has excellently covered the breadth of computational neuroscience from statistical interpretations of data to biophysically based modeling of the neurobiological sources of those data. His presentation is clear, pedagogically sound, and readily useable by experts and beginners alike. It is a pleasure to recommend this very well crafted discussion to experimental neuroscientists as well as mathematically well versed Physicists. The book acts as a window to the issues, to the questions, and to the tools for finding the answers to interesting inquiries about brains and how they function." Henry D. I. Abarbanel Physics and Scripps Institution of Oceanography, University of California, San Diego “This book delivers a clear and thorough introduction to sophisticated analysis approaches useful in computational neuroscience. The models described and the examples provided will help readers develop critical intuitions into what the methods reveal about data. The overall approach of the book reflects the extensive experience Prof. Durstewitz has developed as a leading practitioner of computational neuroscience. “ Bruno B. Averbeck
Author: Erik R. Ranschaert
Publisher: Springer
ISBN: 3319948784
Category : Medical
Languages : en
Pages : 369
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Book Description
This book provides a thorough overview of the ongoing evolution in the application of artificial intelligence (AI) within healthcare and radiology, enabling readers to gain a deeper insight into the technological background of AI and the impacts of new and emerging technologies on medical imaging. After an introduction on game changers in radiology, such as deep learning technology, the technological evolution of AI in computing science and medical image computing is described, with explanation of basic principles and the types and subtypes of AI. Subsequent sections address the use of imaging biomarkers, the development and validation of AI applications, and various aspects and issues relating to the growing role of big data in radiology. Diverse real-life clinical applications of AI are then outlined for different body parts, demonstrating their ability to add value to daily radiology practices. The concluding section focuses on the impact of AI on radiology and the implications for radiologists, for example with respect to training. Written by radiologists and IT professionals, the book will be of high value for radiologists, medical/clinical physicists, IT specialists, and imaging informatics professionals.
Author: Olivier Colliot
Publisher: Springer Nature
ISBN: 1071631950
Category : Medical
Languages : en
Pages : 1058
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Book Description
This Open Access volume provides readers with an up-to-date and comprehensive guide to both methodological and applicative aspects of machine learning (ML) for brain disorders. The chapters in this book are organized into five parts. Part One presents the fundamentals of ML. Part Two looks at the main types of data used to characterize brain disorders, including clinical assessments, neuroimaging, electro- and magnetoencephalography, genetics and omics data, electronic health records, mobile devices, connected objects and sensors. Part Three covers the core methodologies of ML in brain disorders and the latest techniques used to study them. Part Four is dedicated to validation and datasets, and Part Five discusses applications of ML to various neurological and psychiatric disorders. In the Neuromethods series style, chapters include the kind of detail and key advice from the specialists needed to get successful results in your laboratory. Comprehensive and cutting, Machine Learning for Brain Disorders is a valuable resource for researchers and graduate students who are new to this field, as well as experienced researchers who would like to further expand their knowledge in this area. This book will be useful to students and researchers from various backgrounds such as engineers, computer scientists, neurologists, psychiatrists, radiologists, and neuroscientists.
