歯科用レジンコンポジットの粘度予測と最適化:ガウス過程回帰とベイズ最適化を用いて
Tomoki Kohno1, Naoya Funayama1, Linghao Xiao1
1Joint Research Laboratory of Advanced Functional Materials Science, Graduate School of Dentistry, The University of Osaka, 1-8 Yamadaoka, Suita, Osaka 565-0871, Japan.
まとめ
機械学習(ガウス過程回帰(GPR)およびベイズ最適化(BO))は、レジンコンポジットの粘度を正確に予測および最適化します。このデータ駆動型アプローチは、臨床用途のための歯科材料のハンドリング特性を向上させます。
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