Handbook of Decision Support Systems for Neurological Disorders
eBook - ePub

Handbook of Decision Support Systems for Neurological Disorders

  1. 320 pages
  2. English
  3. ePUB (mobile friendly)
  4. Available on iOS & Android
eBook - ePub

Handbook of Decision Support Systems for Neurological Disorders

About this book

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

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Yes, you can access Handbook of Decision Support Systems for Neurological Disorders by D. Jude Hemanth in PDF and/or ePUB format, as well as other popular books in Biological Sciences & Biotechnology. We have over one million books available in our catalogue for you to explore.

Table of contents

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