Abstract
This paper presents a novel risk-based method for Automated External Defibrillator (AED) placement. In sudden cardiac events, availability of a nearby AED is crucial for the surviving of cardiac arrest patients. The common method uses historical Out-of-Hospital Cardiac Arrest (OHCA) data for AED placement optimization. But historical data often do not cover the entire area of investigation. The goal of this work is to develop an approach to improve the method based on historical data for AED placement. To this end, we have developed a risk-based method which generates artificial OHCAs based on a risk model. We compare our risk-based method with the one based on historical data using real Singapore OHCA occurrences from Pan-Asian Resuscitation Outcome Study (PAROS). Results show that to deploy a large number of AEDs the risk-based method outperforms the method purely using historical data on the testing dataset. This paper describes our risk-based AED placement method, discusses experimental results, and outlines future work.