عنوان

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

Number

LA71f2f15r

Title Proper

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

General Material Designation

[Article]

First Statement of Responsibility

Lee, Sangil; Mohr, Nicholas M.; Street, W. Nicholas; Nadkarni, Prakash

Title Proper by Another Author

An Overview

Text of Note

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.

Date of Publication

2019

Title

UC Irvine

Electronic name

[Article]

275578

a

Y