New Research: Detection of White Spot Lesions After Orthodontic Treatment Using Artificial Intelligence

New Research: Detection of White Spot Lesions After Orthodontic Treatment Using Artificial Intelligence

???Research Objective?

White spot lesions are common early signs of dental caries in patients undergoing orthodontic treatment. This study aims to detect these lesions using a deep learning-based YOLOv5x algorithm.


???Method and Dataset?

435 post-orthodontic intraoral photographs were manually labeled for white spot lesions. This labeled dataset was used to train and test the deep learning algorithm.


???Performance Metrics and Results

  • Accuracy:?78.6%
  • Recall:?61.8%
  • F1 Score:?69.2%
  • AUC (Area Under the Curve):?71.2%
  • mAP (Mean Average Precision):?42.5%


???Research Findings

The model performed below expectations in detecting white spot lesions but achieved an acceptable accuracy compared to previous studies. These results suggest that with larger datasets and algorithm improvements, enhanced models could be used in clinical settings.


???Conclusion

This pilot study demonstrates the potential use of artificial intelligence in detecting white spot lesions in dentistry. The findings provide a significant foundation for further research and development. The integration of dentistry and artificial intelligence could pave the way for more accurate and rapid diagnostics in the future.


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?? CranioCatch's mission is to improve oral healthcare with AI powered dentistry. CranioCatch is a company composed of passionate employees with an extensive background and experience in the field of AI and dentistry. Our world-class team is passionate about solving tough problems and making an enormous impact in dentistry. Our office is in the Eskisehir city that is located heart of Türkiye.

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