Deep learning in Emergency Medicine: Recent contributions and methodological challenges

  • Francesco Faita | f.faita@ifc.cnr.it Institute of Clinical Physiology, National Research Council, Pisa, Italy.

Abstract

In the last few years, artificial intelligence (AI) technology has grown dramatically impacting several fields of human knowledge and medicine in particular. Among other approaches, deep learning, which is a subset of AI based on specific computational models, such as deep convolutional neural networks and recurrent neural networks, has shown exceptional performance in images and signals processing. Accordingly, emergency medicine will benefit from the adoption of this technology. However, a particular attention should be devoted to the review of these papers in order to exclude overoptimistic results from clinically transferable ones. We presented a group of studies recently published on PubMed and selected by keywords ‘deep learning emergency medicine’ and ‘artificial intelligence emergency medicine’ with the aim of highlighting their methodological strengths and weaknesses, as well as their clinical usefulness.

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Published
2020-03-17
Info
Issue
Section
Reviews
Keywords:
Artificial intelligence, deep learning, emergency medicine
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  • Abstract views: 577

  • PDF: 131
How to Cite
Faita, F. (2020). Deep learning in Emergency Medicine: Recent contributions and methodological challenges. Emergency Care Journal, 16(1). https://doi.org/10.4081/ecj.2020.8573