Machine Learning in Relation to Emergency Medicine Clinical and Operational Scenarios: An Overview

Overview

Journal West J Emerg Med

Specialty Emergency Medicine

Date 2019 Mar 19

PMID 30881539

Citations 16

Authors

Sangil Lee

Nicholas M Mohr

W Nicholas Street

Prakash Nadkarni

Affiliations

Soon will be listed here.

Abstract

Health informatics is a vital technology that holds great promise in the healthcare setting. We describe two prominent health informatics tools relevant to emergency care, as well as the historical background and the current state of informatics. We also identify recent research findings and practice changes. The recent advances in machine learning and natural language processing (NLP) are a prominent development in health informatics overall and relevant in emergency medicine (EM). A basic comprehension of machine-learning algorithms is the key to understand the recent usage of artificial intelligence in healthcare. We are using NLP more in clinical use for documentation. NLP has started to be used in research to identify clinically important diseases and conditions. Health informatics has the potential to benefit both healthcare providers and patients. We cover two powerful tools from health informatics for EM clinicians and researchers by describing the previous successes and challenges and conclude with their implications to emergency care.

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