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Published in: Annals of Intensive Care 1/2019

Open Access 01-12-2019 | Editorial

Predictive analytics: beyond the buzz

Authors: Frederic Michard, Jean Louis Teboul

Published in: Annals of Intensive Care | Issue 1/2019

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Excerpt

Electronic medical records and physiologic monitors produce unprecedented amounts of clinical data, which increasingly powerful computers may turn into novel insights through machine learning and predictive algorithms. Predictive analytics are statistical methods (e.g., random forest models and neural networks) analyzing current and historical data to make predictions about the future. They may detect specific patterns or signatures of clinical deterioration before it becomes overt, opening the door to proactive instead of reactive medicine. As a result, machine learning and predictive analytics, which are subfields of artificial intelligence, are making the buzz in medical journals, congresses, and on the web. In this article, we tried to stay away from novelty blindness to provide a brief evidence-based and balanced overview of opportunities and pitfalls in acute care medicine. …
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Metadata
Title
Predictive analytics: beyond the buzz
Authors
Frederic Michard
Jean Louis Teboul
Publication date
01-12-2019
Publisher
Springer International Publishing
Published in
Annals of Intensive Care / Issue 1/2019
Electronic ISSN: 2110-5820
DOI
https://doi.org/10.1186/s13613-019-0524-9

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