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3. Applications for HADR

4. Basic Framework of HADR

5. Datasets

6. Comparative Analysis

7. Introduction

8. Recent Trends in EEG-Based Epilepsy Detection and Classification: A Comprehensive Review

9. Enhancing EEG-Based Sleep Stage Prediction Using Machine Learning Techniques

10. Comparative Analysis of Machine Learning and Deep Learning Algorithms for Automatic Sleep Staging Using EEG Signals

12. Breast Cancer: Automatic Detection from Mammogram Images by Utilizing Deep Learning Methods

13. Conclusion and Future Directions

14. A Systematic Review on Latest Approaches of Automated Sleep Staging System Using Machine Intelligence Techniques

15. Automatic Breast Cancer Detection with Mammography Approach Using Deep Learning Algorithm

17. A Deep Neural Model CNN-LSTM Network for Automated Sleep Staging Based on a Single-Channel EEG Signal

18. A Machine Learning Model for Automatic Sleep Staging Based on Single-Channel EEG Signals

21. Accurate Machine Learning-Based Automated Sleep Staging Using Clinical Subjects with Suspected Sleep Disorders

22. Automated Sleep Staging System Based on Ensemble Learning Model Using Single-Channel EEG Signal

24. An Automated Sleep Stages Classification Using BrainEEG Signal: A Machine Learning Approaches

25. A Machine Learning Model for Automated Classification of Sleep Stages using Polysomnography Signals

31. A Machine Learning Model for Automated Classification of Sleep Stages Using Polysomnography Signals

32. SleepEEG Study: Automated Sleep Stage Scoring with Machine Learning Techniques from Dual-Channel Brain-EEG Signals

38. Automated Sleep Staging Using Convolution Neural Network Based on Single-Channel EEG Signal

39. Effect of Linear Features to Determination of Sleep Stages Classification from Dual Channel of EEG Signal Using Machine Learning Techniques

40. Automated Sleep Staging of Human Polysomnography Recordings Using Single-Channel of EEG Signals

44. Effect of EEG Dual-Channel Acquisition and Gender Specification Subjects on the Classification of Sleep Stages Using Machine Learning Techniques

45. Automated Sleep Stage Classification Based on Multiple Channels of Electroencephalographic Signals Using Machine Learning Algorithm

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