Evaluating Deep Learning Models for Early Detection of Cardiovascular Diseases in Healthcare Data

1. Introduction 1.1 Background and Motivation 1.2 Objectives of the Study 1.3 Structure of the Thesis 2. Literature Review 2.1 Overview of Cardiovascular Diseases 2.2 Introduction to Deep Learning 2.3 Existing Models in Healthcare 2.4 Challenges in Early Detection 3. Methodology 3.1 Data Collection and Preprocessing 3.2 Model Selection Criteria 3.3 Evaluation Metrics 4. Deep Learning Models 4.1 Convolutional Neural Networks 4.2 Recurrent Neural Networks 4.3 Ensemble Learning Approaches 5. Results and Analysis 5.1 Model Performance Comparison 5.2 Impact of Data Preprocessing 5.3 Case Studies and Observations 6. Discussion 6.1 Interpretation of Findings 6.2 Implications for Healthcare 6.3 Limitations of the Study 7. Recommendations 7.1 Model Improvement Suggestions 7.2 Practical Applications in Medicine 7.3 Future Research Directions 8. Conclusion 8.1 Summary of Findings 8.2 Contribution to the Field 8.3 Final Thoughts and Perspectives