Artificial intelligence (AI) is the study of computer systems capable of performing
tasks that traditionally require human intelligence, and machine learning (ML) is
one mechanism through which an AI system can be developed by creating algorithms that
modify themselves in response to patterns and make inferences when applied to new
data [
1
,
2
,
3
,
4
]. AI has already proven itself to be useful in several fields of medicine, including
radiology, neurosurgery, dermatology, and ophthalmology, in which AI has either matched,
or, in some cases, exceeded the ability of physicians [
5
,
6
,
7
,
- Chen M.C.
- Ball R.L.
- Yang L.
- Moradzadeh N.
- Chapman B.E.
- Larson D.B.
- et al.
Deep learning to classify radiology free-text reports.
Radiology. 2017; 171115https://doi.org/10.1148/radiol.2017171115
8
,
9
,
10
]. Rapidly interpreting clinical data to classify patients and predict outcomes is
paramount to emergency department (ED) operations, with direct impacts on cost, efficiency,
and quality of care. As such, there exists significant potential for improvement in
ED operations through the application of AI.Keywords
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Article Info
Publication History
Published online: January 04, 2018
Accepted:
January 3,
2018
Received:
January 3,
2018
Identification
Copyright
© 2018 Elsevier Inc. All rights reserved.
