A predictive analytics model using machine learning algorithms to estimate the risk of shock development among dengue patients

Highlights

  • This study proposes machine learning algorithms to estimate the risk of shock development among dengue patients.
  • We discuss the performance of different machine learning algorithms and models.
  • We discuss the feature importance to estimate the risk of shock development among dengue patients.
  • Ensemble learnings of bagging and boosting are applied to the weak learner to optimize performance.
  • The experimental results show that the bagging algorithm outperforms other competing methods.

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