Computational Intelligence and Deep Learning Methods for Neuro-rehabilitation Applications

2023-11-17
Computational Intelligence and Deep Learning Methods for Neuro-rehabilitation Applications

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  • Author: D. Jude Hemanth
  • Publisher: Elsevier
  • ISBN: 0443137730
  • Category : Science
  • Languages : en
  • Pages : 304

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

Deep Learning and Other Soft Computing Techniques

2023-06-26
Deep Learning and Other Soft Computing Techniques

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  • Author: Nguyen Hoang Phuong
  • Publisher: Springer Nature
  • ISBN: 3031294475
  • Category : Technology & Engineering
  • Languages : en
  • Pages : 282

This book focuses on the use of artificial intelligence (AI) and computational intelligence (CI) in medical and related applications. Applications include all aspects of medicine: from diagnostics (including analysis of medical images and medical data) to therapeutics (including drug design and radiotherapy) to epidemic- and pandemic-related public health policies. Corresponding techniques include machine learning (especially deep learning), techniques for processing expert knowledge (e.g., fuzzy techniques), and advanced techniques of applied mathematics (such as innovative probabilistic and graph-based techniques). The book also shows that these techniques can be used in many other applications areas, such as finance, transportation, physics. This book helps practitioners and researchers to learn more about AI and CI methods and their biomedical (and related) applications—and to further develop this important research direction.

Advances in Neural Networks

2016-06-18
Advances in Neural Networks

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  • Author: Simone Bassis
  • Publisher: Springer
  • ISBN: 3319337475
  • Category : Technology & Engineering
  • Languages : en
  • Pages : 539

This carefully edited book is putting emphasis on computational and artificial intelligent methods for learning and their relative applications in robotics, embedded systems, and ICT interfaces for psychological and neurological diseases. The book is a follow-up of the scientific workshop on Neural Networks (WIRN 2015) held in Vietri sul Mare, Italy, from the 20th to the 22nd of May 2015. The workshop, at its 27th edition became a traditional scientific event that brought together scientists from many countries, and several scientific disciplines. Each chapter is an extended version of the original contribution presented at the workshop, and together with the reviewers’ peer revisions it also benefits from the live discussion during the presentation. The content of book is organized in the following sections. 1. Introduction, 2. Machine Learning, 3. Artificial Neural Networks: Algorithms and models, 4. Intelligent Cyberphysical and Embedded System, 5. Computational Intelligence Methods for Biomedical ICT in Neurological Diseases, 6. Neural Networks-Based Approaches to Industrial Processes, 7. Reconfigurable Modular Adaptive Smart Robotic Systems for Optoelectronics Industry: The White'R Instantiation This book is unique in proposing a holistic and multidisciplinary approach to implement autonomous, and complex Human Computer Interfaces.

Computational Intelligence for Machine Learning and Healthcare Informatics

2020-06-22
Computational Intelligence for Machine Learning and Healthcare Informatics

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  • Author: Rajshree Srivastava
  • Publisher: Walter de Gruyter GmbH & Co KG
  • ISBN: 3110649276
  • Category : Computers
  • Languages : en
  • Pages : 414

This book presents a variety of techniques designed to enhance and empower multi-disciplinary and multi-institutional machine learning research in healthcare informatics. It is intended to provide a unique compendium of current and emerging machine learning paradigms for healthcare informatics, reflecting the diversity, complexity, and depth and breadth of this multi-disciplinary area.

Trends in Deep Learning Methodologies

2020-11-12
Trends in Deep Learning Methodologies

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  • Author: Vincenzo Piuri
  • Publisher: Academic Press
  • ISBN: 0128232684
  • Category : Computers
  • Languages : en
  • Pages : 308

Trends in Deep Learning Methodologies: Algorithms, Applications, and Systems covers deep learning approaches such as neural networks, deep belief networks, recurrent neural networks, convolutional neural networks, deep auto-encoder, and deep generative networks, which have emerged as powerful computational models. Chapters elaborate on these models which have shown significant success in dealing with massive data for a large number of applications, given their capacity to extract complex hidden features and learn efficient representation in unsupervised settings. Chapters investigate deep learning-based algorithms in a variety of application, including biomedical and health informatics, computer vision, image processing, and more. In recent years, many powerful algorithms have been developed for matching patterns in data and making predictions about future events. The major advantage of deep learning is to process big data analytics for better analysis and self-adaptive algorithms to handle more data. Deep learning methods can deal with multiple levels of representation in which the system learns to abstract higher level representations of raw data. Earlier, it was a common requirement to have a domain expert to develop a specific model for each specific application, however, recent advancements in representation learning algorithms allow researchers across various subject domains to automatically learn the patterns and representation of the given data for the development of specific models. Provides insights into the theory, algorithms, implementation and the application of deep learning techniques Covers a wide range of applications of deep learning across smart healthcare and smart engineering Investigates the development of new models and how they can be exploited to find appropriate solutions

Computational Intelligence and Its Applications in Healthcare

2020-08-01
Computational Intelligence and Its Applications in Healthcare

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  • Author: Jitendra Kumar Verma
  • Publisher: Academic Press
  • ISBN: 0128206195
  • Category : Science
  • Languages : en
  • Pages : 258

Computational Intelligence and Its Applications in Healthcare presents rapidly growing applications of computational intelligence for healthcare systems, including intelligent synthetic characters, man-machine interface, menu generators, user acceptance analysis, pictures archiving, and communication systems. Computational intelligence is the study of the design of intelligent agents, which are systems that act intelligently: they do what they think are appropriate for their circumstances and goals; they're flexible to changing environments and goals; they learn from experience; and they make appropriate choices given perceptual limitations and finite computation. Computational intelligence paradigms offer many advantages in maintaining and enhancing the field of healthcare. Provides coverage of fuzzy logic, neural networks, evolutionary computation, learning theory, probabilistic methods, telemedicine, and robotics applications Includes coverage of artificial intelligence and biological applications, soft computing, image and signal processing, and genetic algorithms Presents the latest developments in computational methods in healthcare Bridges the gap between obsolete literature and current literature

Deep Learning for Medical Decision Support Systems

2020-06-17
Deep Learning for Medical Decision Support Systems

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  • Author: Utku Kose
  • Publisher: Springer Nature
  • ISBN: 981156325X
  • Category : Technology & Engineering
  • Languages : en
  • Pages : 185

This book explores various applications of deep learning-oriented diagnosis leading to decision support, while also outlining the future face of medical decision support systems. Artificial intelligence has now become a ubiquitous aspect of modern life, and especially machine learning enjoysgreat popularity, since it offers techniques that are capable of learning from samples to solve newly encountered cases. Today, a recent form of machine learning, deep learning, is being widely used with large, complex quantities of data, because today’s problems require detailed analyses of more data. This is critical, especially in fields such as medicine. Accordingly, the objective of this book is to provide the essentials of and highlight recent applications of deep learning architectures for medical decision support systems. The target audience includes scientists, experts, MSc and PhD students, postdocs, and any readers interested in the subjectsdiscussed. The book canbe used as a reference work to support courses on artificial intelligence, machine/deep learning, medical and biomedicaleducation.

Computational Neuroscience for Advancing Artificial Intelligence: Models, Methods and Applications

2010-11-30
Computational Neuroscience for Advancing Artificial Intelligence: Models, Methods and Applications

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  • Author: Alonso, Eduardo
  • Publisher: IGI Global
  • ISBN: 1609600231
  • Category : Computers
  • Languages : en
  • Pages : 396

"This book argues that computational models in behavioral neuroscience must be taken with caution, and advocates for the study of mathematical models of existing theories as complementary to neuro-psychological models and computational models"--

Artificial Intelligence in the Age of Neural Networks and Brain Computing

2023-10-27
Artificial Intelligence in the Age of Neural Networks and Brain Computing

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  • Author: Robert Kozma
  • Publisher: Academic Press
  • ISBN: 0323958168
  • Category : Computers
  • Languages : en
  • Pages : 398

Artificial Intelligence in the Age of Neural Networks and Brain Computing, Second Edition demonstrates that present disruptive implications and applications of AI is a development of the unique attributes of neural networks, mainly machine learning, distributed architectures, massive parallel processing, black-box inference, intrinsic nonlinearity, and smart autonomous search engines. The book covers the major basic ideas of "brain-like computing" behind AI, provides a framework to deep learning, and launches novel and intriguing paradigms as possible future alternatives. The present success of AI-based commercial products proposed by top industry leaders, such as Google, IBM, Microsoft, Intel, and Amazon, can be interpreted using the perspective presented in this book by viewing the co-existence of a successful synergism among what is referred to as computational intelligence, natural intelligence, brain computing, and neural engineering. The new edition has been updated to include major new advances in the field, including many new chapters. Developed from the 30th anniversary of the International Neural Network Society (INNS) and the 2017 International Joint Conference on Neural Networks (IJCNN Authored by top experts, global field pioneers, and researchers working on cutting-edge applications in signal processing, speech recognition, games, adaptive control and decision-making Edited by high-level academics and researchers in intelligent systems and neural networks Includes all new chapters, including topics such as Frontiers in Recurrent Neural Network Research; Big Science, Team Science, Open Science for Neuroscience; A Model-Based Approach for Bridging Scales of Cortical Activity; A Cognitive Architecture for Object Recognition in Video; How Brain Architecture Leads to Abstract Thought; Deep Learning-Based Speech Separation and Advances in AI, Neural Networks

Artificial Intelligence for Neurological Disorders

2022-09-23
Artificial Intelligence for Neurological Disorders

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  • Author: Ajith Abraham
  • Publisher: Academic Press
  • ISBN: 0323902782
  • Category : Medical
  • Languages : en
  • Pages : 434

Artificial Intelligence for Neurological Disorders provides a comprehensive resource of state-of-the-art approaches for AI, big data analytics and machine learning-based neurological research. The book discusses many machine learning techniques to detect neurological diseases at the cellular level, as well as other applications such as image segmentation, classification and image indexing, neural networks and image processing methods. Chapters include AI techniques for the early detection of neurological disease and deep learning applications using brain imaging methods like EEG, MEG, fMRI, fNIRS and PET for seizure prediction or neuromuscular rehabilitation. The goal of this book is to provide readers with broad coverage of these methods to encourage an even wider adoption of AI, Machine Learning and Big Data Analytics for problem-solving and stimulating neurological research and therapy advances. Discusses various AI and ML methods to apply for neurological research Explores Deep Learning techniques for brain MRI images Covers AI techniques for the early detection of neurological diseases and seizure prediction Examines cognitive therapies using AI and Deep Learning methods