Machine Learning and Precision Medicine in Emergency Medicine: The Basics

Abstract

As machine learning (ML) and precision medicine become more readily available and used in practice, emergency physicians must understand the potential advantages and limitations of the technology. This narrative review focuses on the key components of machine learning, artificial intelligence, and precision medicine in emergency medicine (EM). Based on the content expertise, we identified articles from EM literature. The authors provided a narrative summary of each piece of literature. Next, the authors provided an introduction of the concepts of ML, artificial intelligence as an extension of ML, and precision medicine. This was followed by concrete examples of their applications in practice and research. Subsequently, we shared our thoughts on how to consume the existing research in these subjects and conduct high-quality research for academic emergency medicine. We foresee that the EM community will continue to adapt machine learning, artificial intelligence, and precision medicine in research and practice. We described several key components using our expertise.

Keywords: artificial intelligence; machine learning; precision medicine; research in emergency medicine; risk prediction.

Figure 1. The framework of deep learning, machine learning, and artificial intelligence

Figure 2. Diagram showing neural network to predict sepsis

Figure 3. Estimate of population covered by primary care facilities using customized catchment areas and dasymetric population obtained from satellite imagery