Machine Learning For Brain Disorders

Download Machine Learning For Brain Disorders full books in PDF, epub, and Kindle. Read online Machine Learning For Brain Disorders ebook anywhere anytime directly on your device. Fast Download speed and no annoying ads. We cannot guarantee that every ebooks is available!

Machine Learning

Author : Andrea Mechelli
Publisher : Academic Press
ISBN 13 : 0128157402
Total Pages : 412 pages
Book Rating : 4.1/5 (281 download)

DOWNLOAD NOW!

Book Synopsis Machine Learning by : Andrea Mechelli

Download or read book Machine Learning written by Andrea Mechelli and published by Academic Press. This book was released on 2019-11-14 with total page 412 pages. Available in PDF, EPUB and Kindle. Book excerpt: Machine Learning is an area of artificial intelligence involving the development of algorithms to discover trends and patterns in existing data; this information can then be used to make predictions on new data. A growing number of researchers and clinicians are using machine learning methods to develop and validate tools for assisting the diagnosis and treatment of patients with brain disorders. Machine Learning: Methods and Applications to Brain Disorders provides an up-to-date overview of how these methods can be applied to brain disorders, including both psychiatric and neurological disease. This book is written for a non-technical audience, such as neuroscientists, psychologists, psychiatrists, neurologists and health care practitioners. Provides a non-technical introduction to machine learning and applications to brain disorders Includes a detailed description of the most commonly used machine learning algorithms as well as some novel and promising approaches Covers the main methodological challenges in the application of machine learning to brain disorders Provides a step-by-step tutorial for implementing a machine learning pipeline to neuroimaging data in Python

Machine Learning

Author : Andrea Mechelli
Publisher : Academic Press
ISBN 13 : 9780128157398
Total Pages : 400 pages
Book Rating : 4.1/5 (573 download)

DOWNLOAD NOW!

Book Synopsis Machine Learning by : Andrea Mechelli

Download or read book Machine Learning written by Andrea Mechelli and published by Academic Press. This book was released on 2019-11 with total page 400 pages. Available in PDF, EPUB and Kindle. Book excerpt: Machine Learning is an area of artificial intelligence involving the development of algorithms to discover trends and patterns in existing data; this information can then be used to make predictions on new data. A growing number of researchers and clinicians are using machine learning methods to develop and validate tools for assisting the diagnosis and treatment of patients with brain disorders. Machine Learning: Methods and Applications to Brain Disorders provides an up-to-date overview of how these methods can be applied to brain disorders, including both psychiatric and neurological disease. This book is written for a non-technical audience, such as neuroscientists, psychologists, psychiatrists, neurologists and health care practitioners. Provides a non-technical introduction to machine learning and applications to brain disorders. Includes a detailed description of the most commonly used machine learning algorithms as well as some novel and promising approaches. Covers the main methodological challenges in the application of machine learning to brain disorders. Provides a step-by-step tutorial for implementing a machine learning pipeline to neuroimaging data in Python.

Machine Learning for Brain Disorders

Author : Olivier Colliot
Publisher : Springer Nature
ISBN 13 : 1071631950
Total Pages : 1058 pages
Book Rating : 4.0/5 (716 download)

DOWNLOAD NOW!

Book Synopsis Machine Learning for Brain Disorders by : Olivier Colliot

Download or read book Machine Learning for Brain Disorders written by Olivier Colliot and published by Springer Nature. This book was released on 2023-07-24 with total page 1058 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Early Detection of Neurological Disorders Using Machine Learning Systems

Author : Paul, Sudip
Publisher : IGI Global
ISBN 13 : 1522585680
Total Pages : 376 pages
Book Rating : 4.5/5 (225 download)

DOWNLOAD NOW!

Book Synopsis Early Detection of Neurological Disorders Using Machine Learning Systems by : Paul, Sudip

Download or read book Early Detection of Neurological Disorders Using Machine Learning Systems written by Paul, Sudip and published by IGI Global. This book was released on 2019-06-28 with total page 376 pages. Available in PDF, EPUB and Kindle. Book excerpt: While doctors and physicians are more than capable of detecting diseases of the brain, the most agile human mind cannot compete with the processing power of modern technology. Utilizing algorithmic systems in healthcare in this way may provide a way to treat neurological diseases before they happen. Early Detection of Neurological Disorders Using Machine Learning Systems provides innovative insights into implementing smart systems to detect neurological diseases at a faster rate than by normal means. The topics included in this book are artificial intelligence, data analysis, and biomedical informatics. It is designed for clinicians, doctors, neurologists, physiotherapists, neurorehabilitation specialists, scholars, academics, and students interested in topics centered on biomedical engineering, bio-electronics, medical electronics, physiology, neurosciences, life sciences, and physics.

Artificial Intelligence for Neurological Disorders

Author : Ajith Abraham
Publisher : Academic Press
ISBN 13 : 0323902782
Total Pages : 434 pages
Book Rating : 4.3/5 (239 download)

DOWNLOAD NOW!

Book Synopsis Artificial Intelligence for Neurological Disorders by : Ajith Abraham

Download or read book Artificial Intelligence for Neurological Disorders written by Ajith Abraham and published by Academic Press. This book was released on 2022-09-23 with total page 434 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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

Recent Progress in Brain and Cognitive Engineering

Author : Seong-Whan Lee
Publisher : Springer
ISBN 13 : 9401772398
Total Pages : 213 pages
Book Rating : 4.4/5 (17 download)

DOWNLOAD NOW!

Book Synopsis Recent Progress in Brain and Cognitive Engineering by : Seong-Whan Lee

Download or read book Recent Progress in Brain and Cognitive Engineering written by Seong-Whan Lee and published by Springer. This book was released on 2015-10-27 with total page 213 pages. Available in PDF, EPUB and Kindle. Book excerpt: For ‘Recent Progress in Brain and Cognitive Engineering’ Brain and Cognitive Engineering is a converging study field to derive a better understanding of cognitive information processing in the human brain, to develop “human-like” and neuromorphic artificial intelligent systems and to help predict and analyze brain-related diseases. The key concept of Brain and Cognitive Engineering is to understand the Brain, to interface the Brain, and to engineer the Brain. It could help us to understand the structure and the key principles of high-order information processing on how the brain works, to develop interface technologies between a brain and external devices and to develop artificial systems that can ultimately mimic human brain functions. The convergence of behavioral, neuroscience and engineering research could lead us to advance health informatics and personal learning, to enhance virtual reality and healthcare systems, and to “reverse engineer” some brain functions and build cognitive robots. In this book, four different recent research directions are presented: Non-invasive Brain-Computer Interfaces, Cognitive- and Neural-rehabilitation Engineering, Big Data Neurocomputing, Early Diagnosis and Prediction of Neural Diseases. We cover numerous topics ranging from smart vehicles and online EEG analysis, neuroimaging for Brain-Computer Interfaces, memory implantation and rehabilitation, big data computing in cultural aspects and cybernetics to brain disorder detection. Hopefully this will provide a valuable reference for researchers in medicine, biomedical engineering, in industry and academia for their further investigations and be inspiring to those who seek the foundations to improve techniques and understanding of the Brain and Cognitive Engineering research field.

Handbook of Decision Support Systems for Neurological Disorders

Author : Hemanth D. Jude
Publisher : Academic Press
ISBN 13 : 0128222727
Total Pages : 320 pages
Book Rating : 4.1/5 (282 download)

DOWNLOAD NOW!

Book Synopsis Handbook of Decision Support Systems for Neurological Disorders by : Hemanth D. Jude

Download or read book Handbook of Decision Support Systems for Neurological Disorders written by Hemanth D. Jude and published by Academic Press. This book was released on 2021-03-30 with total page 320 pages. Available in PDF, EPUB and Kindle. Book excerpt: Handbook of Decision Support Systems for Neurological Disorders provides readers with complete coverage of advanced computer-aided diagnosis systems for neurological disorders. While computer-aided decision support systems for different medical imaging modalities are available, this is the first book to solely concentrate on decision support systems for neurological disorders. Due to the increase in the prevalence of diseases such as Alzheimer, Parkinson’s and Dementia, this book will have significant importance in the medical field. Topics discussed include recent computational approaches, different types of neurological disorders, deep convolution neural networks, generative adversarial networks, auto encoders, recurrent neural networks, and modified/hybrid artificial neural networks. Includes applications of computer intelligence and decision support systems for the diagnosis and analysis of a variety of neurological disorders Presents in-depth, technical coverage of computer-aided systems for tumor image classification, Alzheimer’s disease detection, dementia detection using deep belief neural networks, and morphological approaches for stroke detection Covers disease diagnosis for cerebral palsy using auto-encoder approaches, contrast enhancement for performance enhanced diagnosis systems, autism detection using fuzzy logic systems, and autism detection using generative adversarial networks Written by engineers to help engineers, computer scientists, researchers and clinicians understand the technology and applications of decision support systems for neurological disorders

Big Data in Psychiatry and Neurology

Author : Ahmed Moustafa
Publisher : Academic Press
ISBN 13 : 0128230029
Total Pages : 386 pages
Book Rating : 4.1/5 (282 download)

DOWNLOAD NOW!

Book Synopsis Big Data in Psychiatry and Neurology by : Ahmed Moustafa

Download or read book Big Data in Psychiatry and Neurology written by Ahmed Moustafa and published by Academic Press. This book was released on 2021-06-11 with total page 386 pages. Available in PDF, EPUB and Kindle. Book excerpt: Big Data in Psychiatry and Neurology provides an up-to-date overview of achievements in the field of big data in Psychiatry and Medicine, including applications of big data methods to aging disorders (e.g., Alzheimer’s disease and Parkinson’s disease), mood disorders (e.g., major depressive disorder), and drug addiction. This book will help researchers, students and clinicians implement new methods for collecting big datasets from various patient populations. Further, it will demonstrate how to use several algorithms and machine learning methods to analyze big datasets, thus providing individualized treatment for psychiatric and neurological patients. As big data analytics is gaining traction in psychiatric research, it is an essential component in providing predictive models for both clinical practice and public health systems. As compared with traditional statistical methods that provide primarily average group-level results, big data analytics allows predictions and stratification of clinical outcomes at an individual subject level. Discusses longitudinal big data and risk factors surrounding the development of psychiatric disorders Analyzes methods in using big data to treat psychiatric and neurological disorders Describes the role machine learning can play in the analysis of big data Demonstrates the various methods of gathering big data in medicine Reviews how to apply big data to genetics

Applied Software Development With Python & Machine Learning By Wearable & Wireless Systems For Movement Disorder Treatment Via Deep Brain Stimulation

Download Applied Software Development With Python & Machine Learning By Wearable & Wireless Systems For Movement Disorder Treatment Via Deep Brain Stimulation PDF Online Free

Author : Robert Lemoyne
Publisher : World Scientific
ISBN 13 : 981123597X
Total Pages : 249 pages
Book Rating : 4.8/5 (112 download)

DOWNLOAD NOW!

Book Synopsis Applied Software Development With Python & Machine Learning By Wearable & Wireless Systems For Movement Disorder Treatment Via Deep Brain Stimulation by : Robert Lemoyne

Download or read book Applied Software Development With Python & Machine Learning By Wearable & Wireless Systems For Movement Disorder Treatment Via Deep Brain Stimulation written by Robert Lemoyne and published by World Scientific. This book was released on 2021-08-26 with total page 249 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book presents the confluence of wearable and wireless inertial sensor systems, such as a smartphone, for deep brain stimulation for treating movement disorders, such as essential tremor, and machine learning. The machine learning distinguishes between distinct deep brain stimulation settings, such as 'On' and 'Off' status. This achievement demonstrates preliminary insight with respect to the concept of Network Centric Therapy, which essentially represents the Internet of Things for healthcare and the biomedical industry, inclusive of wearable and wireless inertial sensor systems, machine learning, and access to Cloud computing resources.Imperative to the realization of these objectives is the organization of the software development process. Requirements and pseudo code are derived, and software automation using Python for post-processing the inertial sensor signal data to a feature set for machine learning is progressively developed. A perspective of machine learning in terms of a conceptual basis and operational overview is provided. Subsequently, an assortment of machine learning algorithms is evaluated based on quantification of a reach and grasp task for essential tremor using a smartphone as a wearable and wireless accelerometer system.Furthermore, these skills regarding the software development process and machine learning applications with wearable and wireless inertial sensor systems enable new and novel biomedical research only bounded by the reader's creativity.Related Link(s)

Intelligent Data Analysis

Author : Deepak Gupta
Publisher : John Wiley & Sons
ISBN 13 : 1119544459
Total Pages : 428 pages
Book Rating : 4.1/5 (195 download)

DOWNLOAD NOW!

Book Synopsis Intelligent Data Analysis by : Deepak Gupta

Download or read book Intelligent Data Analysis written by Deepak Gupta and published by John Wiley & Sons. This book was released on 2020-07-13 with total page 428 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book focuses on methods and tools for intelligent data analysis, aimed at narrowing the increasing gap between data gathering and data comprehension, and emphasis will also be given to solving of problems which result from automated data collection, such as analysis of computer-based patient records, data warehousing tools, intelligent alarming, effective and efficient monitoring, and so on. This book aims to describe the different approaches of Intelligent Data Analysis from a practical point of view: solving common life problems with data analysis tools.

Augmenting Neurological Disorder Prediction and Rehabilitation Using Artificial Intelligence

Author : Anitha S. Pillai
Publisher : Academic Press
ISBN 13 : 0323886264
Total Pages : 356 pages
Book Rating : 4.3/5 (238 download)

DOWNLOAD NOW!

Book Synopsis Augmenting Neurological Disorder Prediction and Rehabilitation Using Artificial Intelligence by : Anitha S. Pillai

Download or read book Augmenting Neurological Disorder Prediction and Rehabilitation Using Artificial Intelligence written by Anitha S. Pillai and published by Academic Press. This book was released on 2022-02-23 with total page 356 pages. Available in PDF, EPUB and Kindle. Book excerpt: Augmenting Neurological Disorder Prediction and Rehabilitation Using Artificial Intelligence focuses on how the neurosciences can benefit from advances in AI, especially in areas such as medical image analysis for the improved diagnosis of Alzheimer’s disease, early detection of acute neurologic events, prediction of stroke, medical image segmentation for quantitative evaluation of neuroanatomy and vasculature, diagnosis of Alzheimer’s Disease, autism spectrum disorder, and other key neurological disorders. Chapters also focus on how AI can help in predicting stroke recovery, and the use of Machine Learning and AI in personalizing stroke rehabilitation therapy. Other sections delve into Epilepsy and the use of Machine Learning techniques to detect epileptogenic lesions on MRIs and how to understand neural networks. Provides readers with an understanding on the key applications of artificial intelligence and machine learning in the diagnosis and treatment of the most important neurological disorders Integrates recent advancements of artificial intelligence and machine learning to the evaluation of large amounts of clinical data for the early detection of disorders such as Alzheimer’s Disease, autism spectrum disorder, Multiple Sclerosis, headache disorder, Epilepsy, and stroke Provides readers with illustrative examples of how artificial intelligence can be applied to outcome prediction, neurorehabilitation and clinical exams, including a wide range of case studies in predicting and classifying neurological disorders

Diagnosis of Neurological Disorders Based on Deep Learning Techniques

Author : Jyotismita Chaki
Publisher : CRC Press
ISBN 13 : 1000872181
Total Pages : 268 pages
Book Rating : 4.0/5 (8 download)

DOWNLOAD NOW!

Book Synopsis Diagnosis of Neurological Disorders Based on Deep Learning Techniques by : Jyotismita Chaki

Download or read book Diagnosis of Neurological Disorders Based on Deep Learning Techniques written by Jyotismita Chaki and published by CRC Press. This book was released on 2023-05-15 with total page 268 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is based on deep learning approaches used for the diagnosis of neurological disorders, including basics of deep learning algorithms using diagrams, data tables, and practical examples, for diagnosis of neurodegenerative and neurodevelopmental disorders. It includes application of feed-forward neural networks, deep generative models, convolutional neural networks, graph convolutional networks, and recurrent neural networks in the field of diagnosis of neurological disorders. Along with this, data preprocessing including scaling, correction, trimming, and normalization is also included. Offers a detailed description of the deep learning approaches used for the diagnosis of neurological disorders. Demonstrates concepts of deep learning algorithms using diagrams, data tables, and examples for the diagnosis of neurodegenerative, neurodevelopmental, and psychiatric disorders. Helps build, train, and deploy different types of deep architectures for diagnosis. Explores data preprocessing techniques involved in diagnosis. Includes real-time case studies and examples. This book is aimed at graduate students and researchers in biomedical imaging and machine learning.

Machine Learning and Deep Learning in Neuroimaging Data Analysis

Author : Anitha S. Pillai
Publisher : CRC Press
ISBN 13 : 1003815545
Total Pages : 133 pages
Book Rating : 4.0/5 (38 download)

DOWNLOAD NOW!

Book Synopsis Machine Learning and Deep Learning in Neuroimaging Data Analysis by : Anitha S. Pillai

Download or read book Machine Learning and Deep Learning in Neuroimaging Data Analysis written by Anitha S. Pillai and published by CRC Press. This book was released on 2024-02-15 with total page 133 pages. Available in PDF, EPUB and Kindle. Book excerpt: Machine learning (ML) and deep learning (DL) have become essential tools in healthcare. They are capable of processing enormous amounts of data to find patterns and are also adopted into methods that manage and make sense of healthcare data, either electronic healthcare records or medical imagery. This book explores how ML/DL can assist neurologists in identifying, classifying or predicting neurological problems that require neuroimaging. With the ability to model high-dimensional datasets, supervised learning algorithms can help in relating brain images to behavioral or clinical observations and unsupervised learning can uncover hidden structures/patterns in images. Bringing together artificial intelligence (AI) experts as well as medical practitioners, these chapters cover the majority of neuro problems that use neuroimaging for diagnosis, along with case studies and directions for future research.

Machine Learning for Medical Image Reconstruction

Author : Farah Deeba
Publisher : Springer Nature
ISBN 13 : 3030615987
Total Pages : 170 pages
Book Rating : 4.0/5 (36 download)

DOWNLOAD NOW!

Book Synopsis Machine Learning for Medical Image Reconstruction by : Farah Deeba

Download or read book Machine Learning for Medical Image Reconstruction written by Farah Deeba and published by Springer Nature. This book was released on 2020-10-21 with total page 170 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the Third International Workshop on Machine Learning for Medical Reconstruction, MLMIR 2020, held in conjunction with MICCAI 2020, in Lima, Peru, in October 2020. The workshop was held virtually. The 15 papers presented were carefully reviewed and selected from 18 submissions. The papers are organized in the following topical sections: deep learning for magnetic resonance imaging and deep learning for general image reconstruction.

Artificial intelligence-based computer-aided diagnosis applications for brain disorders from medical imaging data, volume II

Author : Ahmed Shalaby
Publisher : Frontiers Media SA
ISBN 13 : 2832531008
Total Pages : 121 pages
Book Rating : 4.8/5 (325 download)

DOWNLOAD NOW!

Book Synopsis Artificial intelligence-based computer-aided diagnosis applications for brain disorders from medical imaging data, volume II by : Ahmed Shalaby

Download or read book Artificial intelligence-based computer-aided diagnosis applications for brain disorders from medical imaging data, volume II written by Ahmed Shalaby and published by Frontiers Media SA. This book was released on 2023-08-02 with total page 121 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Signal Processing and Machine Learning for Brain-Machine Interfaces

Author : Toshihisa Tanaka
Publisher : Institution of Engineering and Technology
ISBN 13 : 1785613987
Total Pages : 355 pages
Book Rating : 4.7/5 (856 download)

DOWNLOAD NOW!

Book Synopsis Signal Processing and Machine Learning for Brain-Machine Interfaces by : Toshihisa Tanaka

Download or read book Signal Processing and Machine Learning for Brain-Machine Interfaces written by Toshihisa Tanaka and published by Institution of Engineering and Technology. This book was released on 2018-09 with total page 355 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book introduces signal processing and machine learning techniques for Brain Machine Interfacing/Brain Computer Interfacing (BMI/BCI), and their practical and future applications in neuroscience, medicine, and rehabilitation. This is an emerging and challenging technology in engineering, computing, machine learning, neuroscience and medicine, and so the book will interest researchers, engineers, professionals and specialists from all of these areas who need to know more about cutting edge technologies in the fields.

Artificial Intelligence in the Age of Neural Networks and Brain Computing

Author : Robert Kozma
Publisher : Academic Press
ISBN 13 : 0323958168
Total Pages : 398 pages
Book Rating : 4.3/5 (239 download)

DOWNLOAD NOW!

Book Synopsis Artificial Intelligence in the Age of Neural Networks and Brain Computing by : Robert Kozma

Download or read book Artificial Intelligence in the Age of Neural Networks and Brain Computing written by Robert Kozma and published by Academic Press. This book was released on 2023-10-27 with total page 398 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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