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Biomedical Signals Based Computer-Aided Diagnosis for Neurological Disorders, Murugappan


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Цена: 139750.00T
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Автор: Murugappan
Название:  Biomedical Signals Based Computer-Aided Diagnosis for Neurological Disorders
ISBN: 9783030978471
Издательство: Springer
Классификация:
ISBN-10: 3030978478
Обложка/Формат: Soft cover
Вес: 0.00 кг.
Дата издания: 03.07.2023
Язык: English
Основная тема: Engineering
Ссылка на Издательство: Link
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Поставляется из: Германии
Описание: 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.
Дополнительное описание: 1. Abnormal EEG detection using time-frequency images and convolutional neural network..- 2. Physical action categorization pertaining to certain neurological disorders using machine learning based signal analysis.- 3. A comparative study on EEG features


Biomedical Signals Based Computer-Aided Diagnosis for Neurological Disorders

Автор: Murugappan
Название: Biomedical Signals Based Computer-Aided Diagnosis for Neurological Disorders
ISBN: 3030978443 ISBN-13(EAN): 9783030978440
Издательство: Springer
Рейтинг:
Цена: 139750.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: 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.

Automated EEG-Based Diagnosis of Neurological Disorders

Автор: Adeli
Название: Automated EEG-Based Diagnosis of Neurological Disorders
ISBN: 1138118206 ISBN-13(EAN): 9781138118201
Издательство: Taylor&Francis
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Цена: 73490.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:

Based on the authors' groundbreaking research, Automated EEG-Based Diagnosis of Neurological Disorders: Inventing the Future of Neurology presents a research ideology, a novel multi-paradigm methodology, and advanced computational models for the automated EEG-based diagnosis of neurological disorders. It is based on the ingenious integration of three different computing technologies and problem-solving paradigms: neural networks, wavelets, and chaos theory. The book also includes three introductory chapters that familiarize readers with these three distinct paradigms.

After extensive research and the discovery of relevant mathematical markers, the authors present a methodology for epilepsy diagnosis and seizure detection that offers an exceptional accuracy rate of 96 percent. They examine technology that has the potential to impact and transform neurology practice in a significant way. They also include some preliminary results towards EEG-based diagnosis of Alzheimer's disease.

The methodology presented in the book is especially versatile and can be adapted and applied for the diagnosis of other brain disorders. The senior author is currently extending the new technology to diagnosis of ADHD and autism. A second contribution made by the book is its presentation and advancement of Spiking Neural Networks as the seminal foundation of a more realistic and plausible third generation neural network.


Diagnosis of Neurological Disorders Based on Deep Learning Techniques

Автор: Chaki, Jyotismita
Название: Diagnosis of Neurological Disorders Based on Deep Learning Techniques
ISBN: 1032325232 ISBN-13(EAN): 9781032325231
Издательство: Taylor&Francis
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Цена: 102080.00 T
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Cyberphysical Systems for Epilepsy and Related Brain Disorders

Автор: Nikolaos S. Voros; Christos P. Antonopoulos
Название: Cyberphysical Systems for Epilepsy and Related Brain Disorders
ISBN: 3319200488 ISBN-13(EAN): 9783319200484
Издательство: Springer
Рейтинг:
Цена: 111790.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book introduces a new cyberphysical system that combines clinical and basic neuroscience research with advanced data analysis and medical management tools for developing novel applications for the management of epilepsy.

Автор: Gasm Elseid, Arwa Ahmed , Mohammed Hamza, Alnazie
Название: Computer-Aided Glaucoma Diagnosis System
ISBN: 0367406268 ISBN-13(EAN): 9780367406264
Издательство: Taylor&Francis
Рейтинг:
Цена: 117390.00 T
Наличие на складе: Невозможна поставка.
Описание: Glaucoma is the second leading cause of blindness globally. Early detection and treatment can prevent its progression to avoid total blindness. This book discusses and reviews current approaches for detection and examines new approaches for diagnosis using CAD and machine learning techniques.

Modeling and Analysis of Shape with Applications in Computer-Aided Diagnosis of Breast Cancer

Автор: Guliato Denise, Rangayyan Rangaraj
Название: Modeling and Analysis of Shape with Applications in Computer-Aided Diagnosis of Breast Cancer
ISBN: 1608450325 ISBN-13(EAN): 9781608450329
Издательство: Mare Nostrum (Eurospan)
Рейтинг:
Цена: 33440.00 T
Наличие на складе: Нет в наличии.

EEG-Based Diagnosis of Alzheimer Disease

Автор: Kumar, Nilesh
Название: EEG-Based Diagnosis of Alzheimer Disease
ISBN: 012815392X ISBN-13(EAN): 9780128153925
Издательство: Elsevier Science
Рейтинг:
Цена: 103250.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: EEG-Based Diagnosis of Alzheimer Disease: A Review and Novel Approaches for Feature Extraction and Classification Techniques provides a practical and easy-to-use guide for researchers in EEG signal processing techniques, Alzheimer’s disease, and dementia diagnostics. The book examines different features of EEG signals used to properly diagnose Alzheimer’s Disease early, presenting new and innovative results in the extraction and classification of Alzheimer’s Disease using EEG signals. This book brings together the use of different EEG features, such as linear and nonlinear features, which play a significant role in diagnosing Alzheimer’s Disease.

Medical Image Analysis and Informatics

Название: Medical Image Analysis and Informatics
ISBN: 0367876280 ISBN-13(EAN): 9780367876289
Издательство: Taylor&Francis
Рейтинг:
Цена: 91860.00 T
Наличие на складе: Невозможна поставка.
Описание: The focus of this work is on the implication and applications of CAD (Computer-Aided-Diagnosis) as it relates via medical image analysis to body parts and disease. It details the range and scope of CAD - from head to toe.

Computer-aided design and diagnosis methods for biomedical applications

Название: Computer-aided design and diagnosis methods for biomedical applications
ISBN: 0367638835 ISBN-13(EAN): 9780367638832
Издательство: Taylor&Francis
Рейтинг:
Цена: 137810.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Computer-aided design (CAD) plays a key role in improving biomedical systems for various applications. It also helps in the detection, identification, predication, analysis, and classification of diseases, in the management of chronic conditions, and in the delivery of health services. This book discusses the uses of CAD to solve real-world problems and challenges in biomedical systems with the help of appropriate case studies and research simulation results. Aiming to overcome the gap between CAD and biomedical science, it describes behaviors, concepts, fundamentals, principles, case studies, and future directions for research, including the automatic identification of related disorders using CAD. Features:Proposes CAD for the study of biomedical signals to understand physiology and to improve healthcare systems’ ability to diagnose and identify health disorders. Presents concepts of CAD for biomedical modalities in different disorders. Discusses design and simulation examples, issues, and challenges. Illustrates bio-potential signals and their appropriate use in studying different disorders. Includes case studies, practical examples, and research directions. Computer-Aided Design and Diagnosis Methods for Biometrical Applications is aimed at researchers, graduate students in biomedical engineering, image processing, biomedical technology, medical imaging, and health informatics.

Practical Guide for Biomedical Signals Analysis Using Machine Learning Techniques

Автор: Subasi, Abdulhamit
Название: Practical Guide for Biomedical Signals Analysis Using Machine Learning Techniques
ISBN: 0128174447 ISBN-13(EAN): 9780128174449
Издательство: Elsevier Science
Рейтинг:
Цена: 132500.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:

Practical Guide for Biomedical Signals Analysis Using Machine Learning Techniques: A MATLAB Based Approach presents how machine learning and biomedical signal processing methods can be used in biomedical signal analysis. Different machine learning applications in biomedical signal analysis, including those for electrocardiogram, electroencephalogram and electromyogram are described in a practical and comprehensive way, helping readers with limited knowledge. Sections cover biomedical signals and machine learning techniques, biomedical signals, such as electroencephalogram (EEG), electromyogram (EMG) and electrocardiogram (ECG), different signal-processing techniques, signal de-noising, feature extraction and dimension reduction techniques, such as PCA, ICA, KPCA, MSPCA, entropy measures, and other statistical measures, and more.

This book is a valuable source for bioinformaticians, medical doctors and other members of the biomedical field who need a cogent resource on the most recent and promising machine learning techniques for biomedical signals analysis.

  • Provides comprehensive knowledge in the application of machine learning tools in biomedical signal analysis for medical diagnostics, brain computer interface and man/machine interaction
  • Explains how to apply machine learning techniques to EEG, ECG and EMG signals
  • Gives basic knowledge on predictive modeling in biomedical time series and advanced knowledge in machine learning for biomedical time series

Circuits, Signals and Systems for Bioengineers

Автор: Semmlow, John
Название: Circuits, Signals and Systems for Bioengineers
ISBN: 0128093951 ISBN-13(EAN): 9780128093955
Издательство: Elsevier Science
Рейтинг:
Цена: 106660.00 T
Наличие на складе: Нет в наличии.
Описание:

Circuits, Signals and Systems for Bioengineers: A MATLAB-Based Introduction, Third Edition, guides the reader through the electrical engineering principles that can be applied to biological systems. It details the basic engineering concepts that underlie biomedical systems, medical devices, biocontrol and biomedical signal analysis, providing a solid foundation for students in important bioengineering concepts.

Fully revised and updated to better meet the needs of instructors and students, the third edition introduces and develops concepts through computational methods that allow students to explore operations, such as correlations, convolution, the Fourier transform and the transfer function. New chapters have been added on image analysis, noise, stochastic processes and ergodicity, and new medical examples and applications are included throughout the text.


  • Covers current applications in biocontrol, with examples from physiological systems modeling, such as the respiratory system
  • Includes revised material throughout, with improved clarity of presentation and more biological, physiological and medical examples and applications
  • Includes a new chapter on noise, stochastic processes, non-stationary and ergodicity
  • Includes a separate new chapter featuring expanded coverage of image analysis
  • Includes support materials, such as solutions, lecture slides, MATLAB data and functions needed to solve the problems

Histone Deacetylase Inhibitors — Epidrugs for Neurological Disorders

Автор: Shabir Ahmad Ganai
Название: Histone Deacetylase Inhibitors — Epidrugs for Neurological Disorders
ISBN: 981138018X ISBN-13(EAN): 9789811380181
Издательство: Springer
Рейтинг:
Цена: 130430.00 T
Наличие на складе: Нет в наличии.
Описание: This book provides an outline of epigenetics as a whole, while also specifically examining a range of epigenetic players, including histone acetyl transferases (HATs) and histone deacetylases (HDACs). It chiefly focuses on the emerging targets of HDACs and their implications for various neurological disorders, while also discussing the drawbacks of current therapeutic strategies, the classification of HDAC inhibitors, and their promising effects in connection with specific neurological disorders. The book explores the potential use of these inhibitors as novel therapeutic agents, considers the current challenges involved in using them to tackle neurological complications, and offers a novel solution by designing isoform-selective inhibitors and employing combinatorial therapeutic strategies. Its final section, which explores future directions, elaborates on the possibility of enhancing HDAC inhibitors’ therapeutic efficacy against various neurological complications.


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