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.
Les mer
1. Early detection of neurological diseases using machine learning and deep learning techniques: A review
2. A predictive method for emotional sentiment analysis by deep learning from EEG of brainwave data
3. Machine learning and deep learning models for early-stage detection of Alzheimer's disease and its proliferation in human brain
4. Recurrent neural network model for identifying epilepsy based neurological auditory disorder
5. Recurrent neural network model for identifying neurological auditory disorder
6. Dementia diagnosis with EEG using machine learning
7. Computational methods for translational brain-behavior analysis
8. Clinical applications of deep learning in neurology and its enhancements with future directions
9. Ensemble sparse intelligent mining techniques for cognitive disease
10. Cognitive therapy for brain diseases using deep learning models
11. Cognitive therapy for brain diseases using artificial intelligence models
12. Clinical applications of deep learning in neurology and its enhancements with future predictions
13. An intelligent diagnostic approach for epileptic seizure detection and classification using machine learning
14. Neural signaling and communication using machine learning
15. Classification of neurodegenerative disorders using machine learning techniques
16. New trends in deep learning for neuroimaging analysis and disease prediction
17. Prevention and diagnosis of neurodegenerative diseases using machine learning models
18. Artificial intelligence-based early detection of neurological disease using noninvasive method based on speech analysis
19. An insight into applications of deep learning in neuroimaging
20. Incremental variance learning-based ensemble classification model for neurological disorders
21. Early detection of Parkinsons disease using adaptive machine learning techniques: A review
22. Convolutional neural network model for identifying neurological visual disorder
Les mer
A comprehensive reference of AI and machine learning-based methods and techniques for neurological research
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
Les mer
Produktdetaljer
ISBN
9780323902779
Publisert
2022-09-22
Utgiver
Vendor
Academic Press Inc
Vekt
450 gr
Høyde
229 mm
Bredde
152 mm
Aldersnivå
P, 06
Språk
Product language
Engelsk
Format
Product format
Heftet
Antall sider
432