Assessing the Effectiveness of Artificial Intelligence in Detecting Alveolar Bone Loss in Periodontal Disease

Introduction

• Importance of early detection in periodontal disease.
• AI as a tool for improving diagnostic accuracy.

Data Collection and Study Design

• Retrospective evaluation of radiology data.
• Inclusion and exclusion criteria for image quality.
• Use of standardized panoramic imaging device.

Methodology

• Segmentation of bone loss areas on panoramic images.
• Standardized radiography parameters.
• Data anonymization before analysis.

Evaluation of AI Model

• Testing a PyTorch model on a 10% test dataset.
• Comparison of AI model accuracy with radiologist assessment.
• Confusion matrix used for performance assessment.

Results

• Metrics for true positives, true negatives, false positives, and false negatives.
• Discussion on regional vs. general detection success.

Discussion

• Implications for periodontal classification and diagnosis.
• Benefits of AI in improving periodontal disease detection.

Conclusion

• Summary of AI's effectiveness in detecting alveolar bone loss.
• Recommendations for future research and clinical use of AI.

Author Contributions

• Contributions of each author and proofreading acknowledgment.

Funding and Ethical Considerations

• No external funding received.
• Compliance with ethical standards and informed consent from participants.