Artificial Intelligence for Neurological Disorders

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. 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 INDICE: 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. Windowed MDC Transform based Textural Descriptor approach for Voice Disorder Detection 4. Recurrent Neural Network Model for Identifying Neurological Auditory Disorder 5. Convolutional Neural Network Model for Identifying Neurological Visual 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 Non-Invasive Method Based on Speech Analysis 19. Clinical applications of deep learning in neurology and its enhancements with future predictions 20. Machine Learning based Prevention and Diagnosis of Neurodegenerative Diseases 21. An Insight into Applications of Deep learning to neuroimaging 22. Incremental variance learning based ensemble classification model for neurological disorders 23. Early Detection of Parkinson Disease using adaptive machine learning techniques: A Review

• ISBN: 978-0-323-90277-9
• Editorial: Academic Press
• Encuadernacion: Rústica
• Páginas: 500
• Fecha Publicación: 01/09/2022
• Nº Volúmenes: 1
• Idioma: Inglés