The Length of Stay (LoS) refers to the time between a patient’s hospital admission and discharge. LoS is considered to increase as the complexity of the disease increases. A prolonged stay in the Intensive Care Unit (ICU) can consume clinical resources and be labor intensive.

Models that correctly predict LoS are needed to help medical experts make better decisions.

To define an ideal process system, healthcare models must consider the patient’s condition, availability of beds, resources, etc.

These predictions can also help insurance companies manage their budgets.

Existing models deploy machines and deep learning techniques to predict LoS.

However, there is a need for improvement, considering the features associated with the process.

This study presents machine learning algorithms, such as SVM and a stack ensemble, with improved accuracy over existing models.

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