Early Detection Of Neurological Disorders Using Machine Learning Systems

Author : Paul, Sudip,Bhattacharya, Pallab,Bit, Arindam
Publisher : IGI Global
Page : 376 pages
File Size : 40,8 Mb
Release : 2019-06-28
Category : Medical
ISBN : 9781522585688

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Early Detection of Neurological Disorders Using Machine Learning Systems by Paul, Sudip,Bhattacharya, Pallab,Bit, Arindam Pdf

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,Sujata Dash,Subhendu Kumar Pani,Laura García-Hernández
Publisher : Academic Press
Page : 434 pages
File Size : 55,8 Mb
Release : 2022-09-23
Category : Medical
ISBN : 9780323902786

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Artificial Intelligence for Neurological Disorders by Ajith Abraham,Sujata Dash,Subhendu Kumar Pani,Laura García-Hernández Pdf

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 : Anitha S. Pillai,Bindu Menon
Publisher : Academic Press
Page : 356 pages
File Size : 53,6 Mb
Release : 2022-02-23
Category : Science
ISBN : 9780323886260

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Augmenting Neurological Disorder Prediction and Rehabilitation Using Artificial Intelligence by Anitha S. Pillai,Bindu Menon Pdf

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
Page : 268 pages
File Size : 49,6 Mb
Release : 2023-05-15
Category : Computers
ISBN : 9781000872187

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Diagnosis of Neurological Disorders Based on Deep Learning Techniques by Jyotismita Chaki Pdf

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 : Hemanth D. Jude
Publisher : Academic Press
Page : 320 pages
File Size : 55,9 Mb
Release : 2021-03-30
Category : Science
ISBN : 9780128222720

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Handbook of Decision Support Systems for Neurological Disorders by Hemanth D. Jude Pdf

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 : Deepika Koundal,Deepak Kumar Jain,Yanhui Guo,Amira S. Ashour,Atef Zaguia
Publisher : Springer Nature
Page : 267 pages
File Size : 48,7 Mb
Release : 2023-05-31
Category : Medical
ISBN : 9789819921546

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Data Analysis for Neurodegenerative Disorders by Deepika Koundal,Deepak Kumar Jain,Yanhui Guo,Amira S. Ashour,Atef Zaguia Pdf

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 : Rodriguez, Raul Villamarin,Kannan, Hemachandran,T., Revathi,Shaikh, Khalid,Bekal, Sreelekshmi
Publisher : IGI Global
Page : 346 pages
File Size : 49,8 Mb
Release : 2024-02-14
Category : Medical
ISBN : 9798369312827

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Deep Learning Approaches for Early Diagnosis of Neurodegenerative Diseases by Rodriguez, Raul Villamarin,Kannan, Hemachandran,T., Revathi,Shaikh, Khalid,Bekal, Sreelekshmi Pdf

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 : Andrea Mechelli,Sandra Vieira
Publisher : Academic Press
Page : 412 pages
File Size : 51,5 Mb
Release : 2019-11-14
Category : Medical
ISBN : 9780128157404

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Machine Learning by Andrea Mechelli,Sandra Vieira Pdf

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 : Loveleen Gaur
Publisher : Springer Nature
Page : 184 pages
File Size : 55,6 Mb
Release : 2024-06-01
Category : Electronic
ISBN : 9783031531484

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AI and Neuro-Degenerative Diseases by Loveleen Gaur Pdf

Author : Gupta, Shweta
Publisher : IGI Global
Page : 309 pages
File Size : 46,5 Mb
Release : 2022-02-11
Category : Technology & Engineering
ISBN : 9781799895367

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Bio-Inspired Algorithms and Devices for Treatment of Cognitive Diseases Using Future Technologies by Gupta, Shweta Pdf

As there are no proper medical tests available to predict certain diseases such as Alzheimer’s and Parkinson’s at an early stage, there is a need to further study and consider the potential uses of bio- and nature-inspired algorithms and future technologies such as machine learning in correlation to disease detection and treatment. Bio-Inspired Algorithms and Devices for Treatment of Cognitive Diseases Using Future Technologies considers new tools for early detection of cognitive brain diseases using devices and algorithms whose basic concept is taken from nature and discusses design, analysis, and application of various bionics or bio-inspired algorithms. Covering topics such as depression and cognitive science, this publication is an ideal resource for researchers, academicians, industry professionals, psychologists, psychiatrists, nurses, engineers, instructors, and students.

Author : M. Murugappan,Yuvaraj Rajamanickam
Publisher : Springer Nature
Page : 295 pages
File Size : 45,5 Mb
Release : 2022-06-17
Category : Technology & Engineering
ISBN : 9783030978457

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Biomedical Signals Based Computer-Aided Diagnosis for Neurological Disorders by M. Murugappan,Yuvaraj Rajamanickam Pdf

Biomedical signals provide unprecedented insight into abnormal or anomalous neurological conditions. The computer-aided diagnosis (CAD) system plays a key role in detecting neurological abnormalities and improving diagnosis and treatment consistency in medicine. This book covers different aspects of biomedical signals-based systems used in the automatic detection/identification of neurological disorders. Several biomedical signals are introduced and analyzed, including electroencephalogram (EEG), electrocardiogram (ECG), heart rate (HR), magnetoencephalogram (MEG), and electromyogram (EMG). It explains the role of the CAD system in processing biomedical signals and the application to neurological disorder diagnosis. The book provides the basics of biomedical signal processing, optimization methods, and machine learning/deep learning techniques used in designing CAD systems for neurological disorders.

Author : Kumar, Abhishek,Ahuja, Sachin,Baliyan, Anupam,Annawati, Sreenatha,Anand, Abhineet
Publisher : IGI Global
Page : 412 pages
File Size : 48,6 Mb
Release : 2024-02-08
Category : Medical
ISBN : 9798369311165

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Intelligent Technologies and Parkinson’s Disease: Prediction and Diagnosis by Kumar, Abhishek,Ahuja, Sachin,Baliyan, Anupam,Annawati, Sreenatha,Anand, Abhineet Pdf

When it comes to Parkinson's disease, one of the most important issues revolves around early detection and accurate diagnosis. The intricacies of this neurodegenerative disorder often elude timely identification, leaving patients and healthcare providers grappling with its progressive symptoms. Ethical concerns surrounding the use of machine learning to aid in diagnosis further complicate this challenge. This issue is particularly significant for research scholars, PhD fellows, post-doc fellows, and medical and biomedical scholars seeking to unravel the mysteries of Parkinson's disease and develop more effective treatments. Intelligent Technologies and Parkinson’s Disease: Prediction and Diagnosis serves as a beacon of hope in the quest to revolutionize Parkinson's disease diagnosis and treatment. It unveils the remarkable potential of artificial intelligence (AI) and machine learning (ML) in remodeling the way we approach this debilitating condition. With a comprehensive exploration of AI's capacity to analyze speech patterns, brain imaging data, and gait patterns, this book offers a powerful solution to the challenges of early detection and accurate diagnosis.

Author : Saman Sargolzaei,Ali Fatemi,Fahimeh Mamashli,Anna Farzindar,Yalda Mohsenzadeh,Arman Sargolzaei
Publisher : Frontiers Media SA
Page : 134 pages
File Size : 43,8 Mb
Release : 2022-12-02
Category : Science
ISBN : 9782832508480

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Deep Learning for Neurological Disorders in Children by Saman Sargolzaei,Ali Fatemi,Fahimeh Mamashli,Anna Farzindar,Yalda Mohsenzadeh,Arman Sargolzaei Pdf

Author : Deepak Gupta,Siddhartha Bhattacharyya,Ashish Khanna,Kalpna Sagar
Publisher : John Wiley & Sons
Page : 428 pages
File Size : 52,9 Mb
Release : 2020-07-13
Category : Technology & Engineering
ISBN : 9781119544456

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Intelligent Data Analysis by Deepak Gupta,Siddhartha Bhattacharyya,Ashish Khanna,Kalpna Sagar Pdf

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.

Author : Anitha S. Pillai,Bindu Menon
Publisher : CRC Press
Page : 133 pages
File Size : 45,9 Mb
Release : 2024-02-15
Category : Computers
ISBN : 9781003815549

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Machine Learning and Deep Learning in Neuroimaging Data Analysis by Anitha S. Pillai,Bindu Menon Pdf

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.