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Machine learning in dentistry and oral surgery: charting the course with bibliometric insights
3
Zitationen
6
Autoren
2025
Jahr
Abstract
ML has made remarkable progress in dentistry and oral surgery. Although clinicians can benefit from the application of ML models in their practice, they should conduct comprehensive clinical validations to ensure the accuracy and reliability of these models. Moreover, challenges, such as data availability and security, algorithmic biases, and "black-box models", must be addressed. Future research should focus on integrating multimodal data and leveraging foundation models to improve the accuracy of diagnosis, treatment planning, and educational tools in dentistry and oral surgery.
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