Handbook of Decision Support Systems for Neurological Disorders

Handbook of Decision Support Systems for Neurological Disorders

1st Edition - March 30, 2021

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  • Editor: Jude Hemanth
  • Paperback ISBN: 9780128222713
  • eBook ISBN: 9780128222720

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Description

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.

Key Features

  • 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

Readership

Biomedical Engineers and researchers in neural engineering, biomedical engineering, computer science, and mathematics. Clinicians and researchers in neuroscience

Table of Contents

  • 1.A review of deep learning-based disease detection in Alzheimer’s patients
    2. Brain tissue segmentation to detect schizophrenia in gray matter using MR images
    3. Detection of small tumors of the brain using medical imaging
    4. Fuzzy logic-based hybrid knowledge systems for the detection and diagnosis of childhood autism
    5. Artificial intelligence for risk prediction of Alzheimer’s disease: a new promise for community health screening in the
    older aged
    6. Cost-effective assistive device for motor neuron disease
    7. EEG signal-based human emotion detection using an artificial neural network
    8. Multiview decision tree-based segmentation of tumors in MR brain medical images
    9. Multiclass SVM coupled with optimization techniques for
    segmentation and classification of medical images
    10. Brain tissues segmentation in magnetic resonance imaging for the diagnosis of brain disorders using a convolutional neural network
    11. Fine motor skills and cognitive development using virtual reality-based games in children
    12. A CAD software application as a decision support system for ischemic stroke detection in the posterior fossa
    13. Optimization-based multilevel threshold image segmentation for identifying ischemic stroke lesion in brain MR images
    14. A study of machine learning algorithms used for detecting cognitive disorders associated with dyslexia
    15. A Critical Analysis and Review of Assistive Technology: Advancements, Laws, and Impact on Improving the Rehabilitation of Dysarthric Patients
    16. A comparative study on the application of machine learning
    algorithms for neurodegenerative disease prediction

Product details

  • No. of pages: 320
  • Language: English
  • Copyright: © Academic Press 2021
  • Published: March 30, 2021
  • Imprint: Academic Press
  • Paperback ISBN: 9780128222713
  • eBook ISBN: 9780128222720

About the Editor

Jude Hemanth

Dr. D. Jude Hemanth received his PhD in Medical Image Analysis Using Soft Computing Techniques from Karunya University, India. He currently is an Associate Professor at Karunya University with research interests in Soft Computing, Biomedical Image Processing, and Optimization Techniques. He lectures on Biomedical Instrumentation, Neural Networks, Fuzzy Systems, Soft Computing, Digital Image Processing, and Multimedia Compression Techniques. He has been a prolific author and editor of many books and book chapters, including Nature Inspired Optimization Techniques for Image Processing Applications, Springer; Imaging and Sensing for Unmanned Aerial Vehicles, Institution of Engineering and Technology; Intelligent Data Communication Technologies and Internet of Things, Springer; Artificial Intelligence Techniques for Satellite Image Analysis, Springer, Emerging Trends in Computing and Expert Technology, Springer; Artificial Intelligence Techniques for Medical Image Analysis, VDM Verlag; Intelligent Data Analysis for Biomedical Applications, Academic Press; and Telemedicine Technologies, Academic Press, among others.

Affiliations and Expertise

Associate Professor, Karunya University, Tamil Nadu, India

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