Developing Machine Learning Models for Automated Detection of Eye Diseases in High-resolution Images

1. Introduction 1.1 Background and Motivation 1.2 Research Objectives 1.3 Structure of the Work 2. Literature Review 2.1 Overview of Eye Diseases 2.2 Machine Learning in Medical Imaging 2.3 High-resolution Image Analysis 3. Methodology 3.1 Data Collection and Preprocessing 3.2 Model Selection Criteria 3.3 Training and Validation Process 4. Model Development 4.1 Architecture of the Models 4.2 Feature Extraction Techniques 4.3 Hyperparameter Tuning 5. Experimental Setup 5.1 Hardware and Software Used 5.2 Experimental Protocol 5.3 Evaluation Metrics 6. Results and Discussion 6.1 Performance Analysis 6.2 Comparison with Existing Models 6.3 Interpretability of Results 7. Challenges and Limitations 7.1 Data-related Challenges 7.2 Technical Limitations 7.3 Ethical Considerations 8. Conclusion and Future Work 8.1 Summary of Findings 8.2 Implications for Practice 8.3 Directions for Future Research