Primer on machine learning: utilization of large data set analyses to individualize pain management.

Clicks: 380
ID: 5011
2019
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Ranked #2 of 26 articles by views in current opinion in anaesthesiology

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Abstract
Pain researchers and clinicians increasingly encounter machine learning algorithms in both research methods and clinical practice. This review provides a summary of key machine learning principles, as well as applications to both structured and unstructured datasets.Aside from increasing use in the analysis of electronic health record data, machine and deep learning algorithms are now key tools in the analyses of neuroimaging and facial expression recognition data used in pain research.In the coming years, machine learning is likely to become a key component of evidence-based medicine, yet will require additional skills and perspectives for its successful and ethical use in research and clinical settings.
Reference Key
rashidi2019primercurrent Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Rashidi, Parisa;Edwards, David A;Tighe, Patrick J;
Journal current opinion in anaesthesiology
Year 2019
DOI
10.1097/ACO.0000000000000779
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