2024
DOI: 10.1038/s41591-024-02970-3
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Artificial intelligence in surgery

Chris Varghese,
Ewen M. Harrison,
Greg O’Grady
et al.

Abstract: Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

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Cited by 17 publications
(2 citation statements)
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“…The prospective of AI to transform postoperative care extends far beyond free flap monitoring. 7 Artificial intelligence can be trained to identify a wide range of abnormalities in medical images and efficiently summarize and extract critical information from extensive electronic health records. 6 By effectively integrating AI systems into routine postoperative care, clinicians can leverage the power of machine learning to improve patient outcomes across various surgical specialties.…”
Section: + Related Articlementioning
confidence: 99%
See 1 more Smart Citation
“…The prospective of AI to transform postoperative care extends far beyond free flap monitoring. 7 Artificial intelligence can be trained to identify a wide range of abnormalities in medical images and efficiently summarize and extract critical information from extensive electronic health records. 6 By effectively integrating AI systems into routine postoperative care, clinicians can leverage the power of machine learning to improve patient outcomes across various surgical specialties.…”
Section: + Related Articlementioning
confidence: 99%
“…The prospective of AI to transform postoperative care extends far beyond free flap monitoring . Artificial intelligence can be trained to identify a wide range of abnormalities in medical images and efficiently summarize and extract critical information from extensive electronic health records .…”
mentioning
confidence: 99%