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尿路感染症を予測する機械学習アルゴリズム:人口統計データとジップスティック反射率の統合

Julien Favresse1,2, Julien Cabo1, Maxime Bosse1

  • 1Department of Laboratory Medicine, Clinique St-Luc Bouge, Namur, Belgium.

Clinical chemistry
|August 26, 2025
PubMed
まとめ

機械学習モデルは,尿路感染症 (UTI) を高精度で迅速に予測し,不必要な抗生物質の使用を減らす可能性があります. CatBoost Classifierは,従来の方法と比較して,より迅速な尿路感染症の診断に大きな希望を示しています.

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