Machine learning as a construct for artificial intelligence permeates many aspects of our professional lives where it offers the hope to improve health via multiple applications including image recognition, natural or textual language identification, “big data” analysis, and others. While society may not necessarily be completely ready to have their medical care (or automobiles!) usurped by a computer, artificial intelligence has the potential to augment clinical decision-making to enhance safety and improve outcomes. For example, artificial intelligence tools have been created to assist radiologists in reading lung cancer screening computed tomography images and mammograms and have demonstrated significantly better-than-human performance in almost all analyses.

In this issue of Anesthesiology, Maheshwari et al. evaluate whether clinician access to alerts from a hypotension prediction algorithm reduces hypotension compared with usual care. This...

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