
This study demonstrated that Machine learning (ML) is an effective tool for predicting dental adhesives with low and high µTBS values and identifying important chemical features contributing to the µTBS. The ML-based data-driven approach has great potential to accelerate the discovery of new dental adhesives and other dental materials.
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