Interpretation of acid-base metabolism on arterial blood gas samples via machine learning algorithms.

The machine learning models developed exhibited remarkable accuracy, sensitivity, and specificity in predicting the status of acid-base metabolism. However, implementing these models can aid clinicians, freeing up their time for more intricate tasks.