Early Detection Of Neurological Disorders Using Machine Learning Systems

Author : Paul, Sudip
Publisher : IGI Global
ISBN 13 : 1522585680
Total Pages : 376 pages
Book Rating : 4.88/5 ( download)

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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.

Author : Ajith Abraham
Publisher : Academic Press
ISBN 13 : 0323902782
Total Pages : 434 pages
Book Rating : 4.86/5 ( download)

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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

Author : Hemanth D. Jude
Publisher : Academic Press
ISBN 13 : 0128222727
Total Pages : 320 pages
Book Rating : 4.20/5 ( download)

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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

Author : Anitha S. Pillai
Publisher : Academic Press
ISBN 13 : 0323886264
Total Pages : 356 pages
Book Rating : 4.60/5 ( download)

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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

Author : Jyotismita Chaki
Publisher : CRC Press
ISBN 13 : 1000872173
Total Pages : 237 pages
Book Rating : 4.70/5 ( download)

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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 237 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.

Author : Andrea Mechelli
Publisher : Academic Press
ISBN 13 : 0128157402
Total Pages : 412 pages
Book Rating : 4.04/5 ( download)

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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

Author : Deepika Koundal
Publisher : Springer Nature
ISBN 13 : 9819921546
Total Pages : 267 pages
Book Rating : 4.46/5 ( download)

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Download or read book Data Analysis for Neurodegenerative Disorders written by Deepika Koundal and published by Springer Nature. This book was released on 2023-05-31 with total page 267 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book explores the challenges involved in handling medical big data in the diagnosis of neurological disorders. It discusses how to optimally reduce the number of neuropsychological tests during the classification of these disorders by using feature selection methods based on the diagnostic information of enrolled subjects. The book includes key definitions/models and covers their applications in different types of signal/image processing for neurological disorder data. An extensive discussion on the possibility of enhancing the abilities of AI systems using the different data analysis is included. The book recollects several applicable basic preliminaries of the different AI networks and models, while also highlighting basic processes in image processing for various neurological disorders. It also reports on several applications to image processing and explores numerous topics concerning the role of big data analysis in addressing signal and image processing in various real-world scenarios involving neurological disorders. This cutting-edge book highlights the analysis of medical data, together with novel procedures and challenges for handling neurological signals and images. It will help engineers, researchers and software developers to understand the concepts and different models of AI and data analysis. To help readers gain a comprehensive grasp of the subject, it focuses on three key features: ● Presents outstanding concepts and models for using AI in clinical applications involving neurological disorders, with clear descriptions of image representation, feature extraction and selection. ● Highlights a range of techniques for evaluating the performance of proposed CAD systems for the diagnosis of neurological disorders. ● Examines various signal and image processing methods for efficient decision support systems. Soft computing, machine learning and optimization algorithms are also included to improve the CAD systems used.

Author : Muhammed Niyas
Publisher : Meem Publishers
ISBN 13 : 9786176179368
Total Pages : 0 pages
Book Rating : 4.6X/5 ( download)

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Download or read book Early Alzheimer's Detection with Machine Learning written by Muhammed Niyas and published by Meem Publishers. This book was released on 2023-07-11 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Alzheimer's Disease is a progressive neurodegenerative disorder that affects millions of people worldwide. Detecting this condition in its early stages is critical for timely intervention and better management of the disease. "Early Detection of Alzheimer's Disease using Machine Learning Algorithms" presents a groundbreaking approach to identify early signs of Alzheimer's through advanced machine learning techniques. By harnessing the power of machine learning algorithms, this innovative system analyzes vast amounts of data, including cognitive assessments, brain imaging, and genetic markers. The algorithms can recognize subtle patterns and anomalies indicative of Alzheimer's disease, even before noticeable symptoms manifest. This cutting-edge technology holds great promise in transforming healthcare by enabling early identification of Alzheimer's, potentially leading to more effective treatments and therapies. Moreover, it can provide valuable insights for researchers and medical professionals to better understand the disease's progression and improve patient care. The utilization of machine learning algorithms not only enhances the accuracy and efficiency of Alzheimer's detection but also expedites the diagnostic process, reducing the burden on both patients and healthcare providers. As this field continues to evolve, the application of machine learning in Alzheimer's detection brings hope for a future with improved quality of life for those affected by this challenging condition. Early Alzheimer's Detection with Machine Learning represents a significant leap in the fight against Alzheimer's, offering a beacon of hope for early intervention, better care, and improved outcomes for individuals and their families facing this debilitating disease.

Author : Rodriguez, Raul Villamarin
Publisher : IGI Global
ISBN 13 :
Total Pages : 346 pages
Book Rating : 4.27/5 ( download)

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Download or read book Deep Learning Approaches for Early Diagnosis of Neurodegenerative Diseases written by Rodriguez, Raul Villamarin and published by IGI Global. This book was released on 2024-02-14 with total page 346 pages. Available in PDF, EPUB and Kindle. Book excerpt: Within the context of global health challenges posed by intractable neurodegenerative diseases like Alzheimer's and Parkinson's, the significance of early diagnosis is critical for effective intervention, and scientists continue to discover new methods of detection. However, actual diagnosis goes beyond detection to include a significant analysis of combined data for many cases, which presents a challenge of several complicated calculations. Deep Learning Approaches for Early Diagnosis of Neurodegenerative Diseases stands as a groundbreaking work at the intersection of artificial intelligence and neuroscience. The book orchestrates a symphony of cutting-edge techniques and progressions in early detection by assembling eminent experts from the domains of deep learning and neurology. Through a harmonious blend of research areas and pragmatic applications, this monumental work charts the transformative course to revolutionize the landscape of early diagnosis and management of neurodegenerative disorders. Within the pages, readers will embark through the intricate landscape of neurodegenerative diseases, the fundamental underpinnings of deep learning, the nuances of neuroimaging data acquisition and preprocessing, the alchemy of feature extraction and representation learning, and the symphony of deep learning models tailored for neurodegenerative disease diagnosis. The book also delves into integrating multimodal data to augment diagnosis, the imperative of rigorously evaluating and validating deep learning models, and the ethical considerations and challenges entwined with deep learning for neurodegenerative diseases.

Author : Loveleen Gaur
Publisher : Springer Nature
ISBN 13 : 3031531485
Total Pages : 184 pages
Book Rating : 4.84/5 ( download)

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Download or read book AI and Neuro-Degenerative Diseases written by Loveleen Gaur and published by Springer Nature. This book was released on with total page 184 pages. Available in PDF, EPUB and Kindle. Book excerpt: