Explainable Computational Intelligence for Neurological Disorders

1. Artificial Intelligence in Medical-based Systems for Neurological Disorders. 2. A Review on Autonomic Biomarkers in Health and Neurological Disorders: Heart Rate Variability, Skin Conductance, and Entropy-Based Analysis. 3. Advanced Computational Techniques for Neurological Disorder Screening through Wearable Sensor-Based Human Activity Recognition. 4. Sleep Apnea Disorder Detection using Wearable Sensors. 5. An Integrated Study of Biomarkers, Diagnostics and Therapeutic Approaches for Alzheimerâs Disease. 6. Designing Hybrid Models for Neuro-Disease Classification. 7. Interpretability and Explainability of Machine Learning and Deep Learning Models in ECG Disease Detection. 8. Advanced Computational Analysis of Brain Connectivity Using EEG data. 9. Feature Engineering and Machine Learning Approaches for EEG Based Imagined Speech Recognition. 10. Machine Learning Based Huntingtonâs Disease Detection. 11. Clinically Meaningful Epileptic Seizure Prediction Using iEEG Features and Random Forest. 12. Intracranial EEG analysis for predicting Surgery Outcomes of Drug-Resistant Epilepsy subjects using Machine Learning. 13. Explainable Hybrid CNNâ"Transformer Framework for Dynamic Word-Level Indian Sign Language Recognition in Neurological Disorder Communication Assistance Systems. 14. Framework for Design and Evaluation of Virtual Reality based Interventions for Improving Vocational Skills in Individuals with Autism Spectrum Disorder. 15. Stem Cells in Neurology: Advancing Regenerative Therapies for Neurodegenerative Disorders. 16. Integrating Multi-Modal Biomarkers for the Early Detection of Pancreatic Ductal Adenocarcinoma: A Comprehensive Review.