Deep Learning In Aging Neuroscience

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Deep Learning In Aging Neuroscience

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Author : Javier Ramírez
language : en
Publisher: Frontiers Media SA
Release Date : 2020-12-28

Deep Learning In Aging Neuroscience written by Javier Ramírez and has been published by Frontiers Media SA this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-12-28 with Science categories.

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.

Computational Intelligence And Deep Learning Methods For Neuro Rehabilitation Applications

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Author : D. Jude Hemanth
language : en
Publisher: Elsevier
Release Date : 2023-11-14

Computational Intelligence And Deep Learning Methods For Neuro Rehabilitation Applications written by D. Jude Hemanth and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-11-14 with Science categories.

Computational Intelligence and Deep Learning Methods for Neuro-rehabilitation Applications explores the different possibilities of providing AI based neuro-rehabilitation methods to treat neurological disorders. This book provides in-depth knowledge on the challenges and solutions associated with the different varieties of neuro-rehabilitation through the inclusion of case studies and real-time scenarios in different geographical locations. Beginning with an overview of neuro-rehabilitation applications, the book discusses the role of machine learning methods in brain function grading for adults with Mild Cognitive Impairment, Brain Computer Interface for post-stroke patients, developing assistive devices for paralytic patients, and cognitive treatment for spinal cord injuries. Topics also include AI-based video games to improve the brain performances in children with autism and ADHD, deep learning approaches and magnetoencephalography data for limb movement, EEG signal analysis, smart sensors, and the application of robotic concepts for gait control. - Incorporates artificial intelligence techniques into neuro-rehabilitation and presents novel ideas for this process - Provides in-depth case studies and state-of-the-art methods, along with the experimental study - Presents a block diagram based complete set-up in each chapter to help in real-time implementation

Machine Learning And Deep Learning Techniques For Medical Image Recognition

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Author : Ben Othman Soufiene
language : en
Publisher: CRC Press
Release Date : 2023-12-01

Machine Learning And Deep Learning Techniques For Medical Image Recognition written by Ben Othman Soufiene and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-12-01 with Technology & Engineering categories.

Machine Learning and Deep Learning Techniques for Medical Image Recognition comprehensively reviews deep learning-based algorithms in medical image analysis problems including medical image processing. It includes a detailed review of deep learning approaches for semantic object detection and segmentation in medical image computing and large-scale radiology database mining. A particular focus is placed on the application of convolutional neural networks with the theory and varied selection of techniques for semantic segmentation using deep learning principles in medical imaging supported by practical examples. Features: Offers important key aspects in the development and implementation of machine learning and deep learning approaches toward developing prediction tools and models and improving medical diagnosis Teaches how machine learning and deep learning algorithms are applied to a broad range of application areas, including chest X-ray, breast computer-aided detection, lung and chest, microscopy, and pathology Covers common research problems in medical image analysis and their challenges Focuses on aspects of deep learning and machine learning for combating COVID-19 Includes pertinent case studies This book is aimed at researchers and graduate students in computer engineering, artificial intelligence and machine learning, and biomedical imaging.

Machine Learning And Deep Learning Techniques For Medical Science

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Author : K. Gayathri Devi
language : en
Publisher: CRC Press
Release Date : 2022-05-11

Machine Learning And Deep Learning Techniques For Medical Science written by K. Gayathri Devi and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-05-11 with Technology & Engineering categories.

The application of machine learning is growing exponentially into every branch of business and science, including medical science. This book presents the integration of machine learning (ML) and deep learning (DL) algorithms that can be applied in the healthcare sector to reduce the time required by doctors, radiologists, and other medical professionals for analyzing, predicting, and diagnosing the conditions with accurate results. The book offers important key aspects in the development and implementation of ML and DL approaches toward developing prediction tools and models and improving medical diagnosis. The contributors explore the recent trends, innovations, challenges, and solutions, as well as case studies of the applications of ML and DL in intelligent system-based disease diagnosis. The chapters also highlight the basics and the need for applying mathematical aspects with reference to the development of new medical models. Authors also explore ML and DL in relation to artificial intelligence (AI) prediction tools, the discovery of drugs, neuroscience, diagnosis in multiple imaging modalities, and pattern recognition approaches to functional magnetic resonance imaging images. This book is for students and researchers of computer science and engineering, electronics and communication engineering, and information technology; for biomedical engineering researchers, academicians, and educators; and for students and professionals in other areas of the healthcare sector. Presents key aspects in the development and the implementation of ML and DL approaches toward developing prediction tools, models, and improving medical diagnosis Discusses the recent trends, innovations, challenges, solutions, and applications of intelligent system-based disease diagnosis Examines DL theories, models, and tools to enhance health information systems Explores ML and DL in relation to AI prediction tools, discovery of drugs, neuroscience, and diagnosis in multiple imaging modalities Dr. K. Gayathri Devi is a Professor at the Department of Electronics and Communication Engineering, Dr. N.G.P Institute of Technology, Tamil Nadu, India. Dr. Kishore Balasubramanian is an Assistant Professor (Senior Scale) at the Department of EEE at Dr. Mahalingam College of Engineering & Technology, Tamil Nadu, India. Dr. Le Anh Ngoc is a Director of Swinburne Innovation Space and Professor in Swinburne University of Technology (Vietnam).

Machine Learning And Deep Learning In Medical Data Analytics And Healthcare Applications

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Author : Om Prakash Jena
language : en
Publisher: CRC Press
Release Date : 2022-02-25

Machine Learning And Deep Learning In Medical Data Analytics And Healthcare Applications written by Om Prakash Jena and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-02-25 with Computers categories.

Machine Learning and Deep Learning in Medical Data Analytics and Healthcare Applications introduces and explores a variety of schemes designed to empower, enhance, and represent multi-institutional and multi-disciplinary machine learning (ML) and deep learning (DL) research in healthcare paradigms. Serving as a unique compendium of existing and emerging ML/DL paradigms for the healthcare sector, this book demonstrates the depth, breadth, complexity, and diversity of this multi-disciplinary area. It provides a comprehensive overview of ML/DL algorithms and explores the related use cases in enterprises such as computer-aided medical diagnostics, drug discovery and development, medical imaging, automation, robotic surgery, electronic smart records creation, outbreak prediction, medical image analysis, and radiation treatments. This book aims to endow different communities with the innovative advances in theory, analytical results, case studies, numerical simulation, modeling, and computational structuring in the field of ML/DL models for healthcare applications. It will reveal different dimensions of ML/DL applications and will illustrate their use in the solution of assorted real-world biomedical and healthcare problems. Features: Covers the fundamentals of ML and DL in the context of healthcare applications Discusses various data collection approaches from various sources and how to use them in ML/DL models Integrates several aspects of AI-based computational intelligence such as ML and DL from diversified perspectives which describe recent research trends and advanced topics in the field Explores the current and future impacts of pandemics and risk mitigation in healthcare with advanced analytics Emphasizes feature selection as an important step in any accurate model simulation where ML/DL methods are used to help train the system and extract the positive solution implicitly This book is a valuable source of information for researchers, scientists, healthcare professionals, programmers, and graduate-level students interested in understanding the applications of ML/DL in healthcare scenarios. Dr. Om Prakash Jena is an Assistant Professor in the Department of Computer Science, Ravenshaw University, Cuttack, Odisha, India. Dr. Bharat Bhushan is an Assistant Professor of Department of Computer Science and Engineering (CSE) at the School of Engineering and Technology, Sharda University, Greater Noida, India. Dr. Utku Kose is an Associate Professor in Suleyman Demirel University, Turkey.

Machine Learning For Neurodegenerative Disorders

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Author : Biswajit Jena
language : en
Publisher: CRC Press
Release Date : 2025-03-31

Machine Learning For Neurodegenerative Disorders written by Biswajit Jena and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-03-31 with Science categories.

This book explores the application of machine learning to the understanding, early diagnosis, and management of neurodegenerative disorders. With a specific focus on its role in ongoing clinical trials, the book covers essential topics such as data collection, pre-processing, feature extraction, model development, and validation techniques. It delves into the applications of neuroimaging techniques like magnetic resonance imaging (MRI), computed tomography (CT), and positron emission tomography (PET) in the diagnosis and understanding of neurodegenerative disorders. Additionally, the book examines various machine-learning algorithms employed for biomarker discovery in neurodegenerative disorders. It highlights the role of neuroinformatics and big data analysis in advancing the understanding and management of neurodegenerative disorders. Furthermore, the book reviews future prospects and presents the ethical considerations and regulatory challenges associated with implementing machine learning approaches in the diagnosis, treatment, and prevention of neurodegenerative disorders. This comprehensive resource is intended for neuroscientists, students, researchers, and neurologists to understand the emerging scope of machine learning in neurodegenerative disorders.

Methods And Applications In Aging Neuroscience

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Author : Yang Jiang
language : en
Publisher: Frontiers Media SA
Release Date : 2023-07-10

Methods And Applications In Aging Neuroscience written by Yang Jiang and has been published by Frontiers Media SA this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-07-10 with Science categories.

Aging

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Author : Paulo J. Oliveira
language : en
Publisher: Academic Press
Release Date : 2022-09-22

Aging written by Paulo J. Oliveira and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-09-22 with Science categories.

Aging: From Fundamental Biology to Societal Impact examines the interconnection of the cellular and molecular basis of aging and societal-based challenges and innovative interventions. Sections take a societal-based angle on aging, describing several flagship initiatives for healthy living and active aging in different regions, cover the biology of aging which includes the hallmarks of aging, explain the pathophysiology of aging, describing different comorbidities associated with aging and possible interventions to decrease the impact of aging, and envision future and innovative measures to tackle aging-related morbidities.Contributions from an interdisciplinary panel of experts cover such topics as the biology of aging to physical activity, nutrition, psychology, pharmacology, health care, social care and urban planning. - Provides a cross-disciplinary approach to aging at both the biological and societal level - Highlights frontline scientific knowledge in the biology of aging and its translation into societal interventions - Offers insights on the value of aging research and its future impact from a fundamental and translation point-of-view

Handbook Of Research On Deep Learning Based Image Analysis Under Constrained And Unconstrained Environments

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Author : Raj, Alex Noel Joseph
language : en
Publisher: IGI Global
Release Date : 2020-12-25

Handbook Of Research On Deep Learning Based Image Analysis Under Constrained And Unconstrained Environments written by Raj, Alex Noel Joseph and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-12-25 with Computers categories.

Recent advancements in imaging techniques and image analysis has broadened the horizons for their applications in various domains. Image analysis has become an influential technique in medical image analysis, optical character recognition, geology, remote sensing, and more. However, analysis of images under constrained and unconstrained environments require efficient representation of the data and complex models for accurate interpretation and classification of data. Deep learning methods, with their hierarchical/multilayered architecture, allow the systems to learn complex mathematical models to provide improved performance in the required task. The Handbook of Research on Deep Learning-Based Image Analysis Under Constrained and Unconstrained Environments provides a critical examination of the latest advancements, developments, methods, systems, futuristic approaches, and algorithms for image analysis and addresses its challenges. Highlighting concepts, methods, and tools including convolutional neural networks, edge enhancement, image segmentation, machine learning, and image processing, the book is an essential and comprehensive reference work for engineers, academicians, researchers, and students.

Deep Learning In Personalized Healthcare And Decision Support

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Author : Harish Garg
language : en
Publisher: Elsevier
Release Date : 2023-07-20

Deep Learning In Personalized Healthcare And Decision Support written by Harish Garg and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-07-20 with Science categories.

Deep Learning in Personalized Healthcare and Decision Support discusses the potential of deep learning technologies in the healthcare sector. The book covers the application of deep learning tools and techniques in diverse areas of healthcare, such as medical image classification, telemedicine, clinical decision support system, clinical trials, electronic health records, precision medication, Parkinson disease detection, genomics, and drug discovery. In addition, it discusses the use of DL for fraud detection and internet of things. This is a valuable resource for researchers, graduate students and healthcare professionals who are interested in learning more about deep learning applied to the healthcare sector. Although there is an increasing interest by clinicians and healthcare workers, they still lack enough knowledge to efficiently choose and make use of technologies currently available. This book fills that knowledge gap by bringing together experts from technology and clinical fields to cover the topics in depth. - Discusses the application of deep learning in several areas of healthcare, including clinical trials, telemedicine and health records management - Brings together experts in the intersection of deep learning, medicine, healthcare and programming to cover topics in an interdisciplinary way - Uncovers the stakes and possibilities involved in realizing personalized healthcare services through efficient and effective deep learning technologies