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. 2023 Apr 1;158(4):337-338.
doi: 10.1001/jamasurg.2022.5444.

Predictive Analytics and Artificial Intelligence in Surgery-Opportunities and Risks

Kathryn Colborn  1 , Gabriel Brat  2 , Rachael Callcut  3
Affiliations

Predictive Analytics and Artificial Intelligence in Surgery-Opportunities and Risks

Kathryn Colborn et al. JAMA Surg. .
No abstract available

Plain language summary

This Viewpoint discusses the opportunities and risks of using 3 main areas of artificial intelligence in surgery: computer vision, digital transformation at the point of care, and electronic health records data.

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Conflict of interest statement

Conflict of Interest Disclosures: Dr Colborn reported grants from the Agency for Healthcare Research and Quality (AHRQ). Dr Callcut reported technology licensed to GE Healthcare, being a cofounder of BeeKeeperAI, a patent for 62/824,183-Federated Machine Learning Techniques for Highly Curated Health-Care Datasets licensed to BeeKeeperAI with royalties paid from University of California, San Francisco, a patent for 051392-Method and Systems for the Automated Detection of Free Fluid Using Artificial Intelligence for the Focused Assessment Sonography for Trauma (“FAST”) Examination for Trauma Care pending University of California, San Francisco hold patent, and grants from GE Healthcare, National Institutes of Health, Philips Health Care to their institution. Some of the work described in this Viewpoint is supported by grant 1R01HS027417 from the AHRQ. No other disclosures were reported.

References

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