# Artificial intelligence to improve patient care in emergency medicine: a workflow-based analysis

## TL;DR

This paper explores how artificial intelligence can improve emergency medicine care by analyzing its applications and risks in both pre-hospital and in-hospital settings.

## Contribution

The paper provides a workflow-based analysis of AI applications in emergency medicine, highlighting both benefits and risks.

## Key findings

- AI can improve pre-hospital care by optimizing ambulance transportation and reducing time outliers.
- AI can assist in hospital settings through imaging analysis and predictive scoring.
- Most studies are small, and a broader discussion is needed to maximize AI benefits while minimizing risks.

## Abstract

In the last years, artificial intelligence has had a strong impact on health sciences, including emergency medicine. There are different fields of application, from pre-hospital to in-hospital issues. Concerning pre-hospital care, it may be useful in controlling patient’ transportation by public ambulance in emergency departments and improve transport time outliers. In hospital management may benefit from its ability to read out imaging or to rapidly calculate predictive scores or suggest therapeutic strategies. While the application of artificial intelligence in emergency medicine is surely intriguing, it is not free from potential risks, which in turn may overcome benefits. Since the majority of the studies are very small rather than pilot, a clear discussion among EM physicians is now necessary in order to better define the application of this technology in the real world by maximizing benefits and reducing risks.