Buch, Englisch, 500 Seiten, Format (B × H): 152 mm x 229 mm, Gewicht: 450 g
Buch, Englisch, 500 Seiten, Format (B × H): 152 mm x 229 mm, Gewicht: 450 g
ISBN: 978-0-323-90277-9
Verlag: William Andrew Publishing
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.
Autoren/Hrsg.
Fachgebiete
Weitere Infos & Material
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