Description
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
