<ul><li>A study was conducted to classify dental providers into standard rendering providers and safety net clinic providers using machine learning models.</li><li>Feature ranking methods were used to identify critical predictors, with treatment-related metrics being identified as the top-ranked features.</li><li>Twelve machine learning models were evaluated, with Neural Network achieving the highest accuracy of 94.1% followed by Gradient Boosting and Random Forest.</li><li>The study emphasizes the importance of feature selection in improving model efficiency and accuracy, especially in imbalanced healthcare datasets.</li></ul>

Classifying Dental Care Providers Through Machine Learning with Features Ranking

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