Fig. 4: Data sources and overview of the machine learning model for predicting out-of-hospital cardiac arrest incidence. | npj Digital Medicine

Fig. 4: Data sources and overview of the machine learning model for predicting out-of-hospital cardiac arrest incidence.

From: Development and evaluation of a machine learning model predicting out-of-hospital cardiac arrest using environmental factors

Fig. 4: Data sources and overview of the machine learning model for predicting out-of-hospital cardiac arrest incidence.

A illustrates the states and communities participating in the Cardiac Arrest Registry to Enhance Survival (CARES). B displays an example of daily maximum ambient temperature data on July 15, 2022, obtained from the North American Land Data Assimilation System (NLDAS). C summarizes the development process of the machine learning model used to predict out-of-hospital cardiac arrest incidence.

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