Machine learning approaches for improvement of patient safety in surgery
2024
Improving Patient Safety in Surgery with Machine Learning
Editorial
Author Information
Author(s): Philip F. Stahel, Kathryn Holland, Roy Nanz
Primary Institution: Mission Health, Asheville, NC, USA
Conclusion
Machine learning and artificial intelligence can significantly enhance patient safety in surgical settings by predicting and preventing adverse events.
Supporting Evidence
- Machine learning can identify patients at risk of harm before adverse events occur.
- AI approaches have shown high sensitivity and specificity in detecting prostate cancer.
- Selected variables can significantly predict the occurrence of surgical 'never events'.
- The Rothman Index is a sensitive predictor of unplanned ICU readmissions.
- Machine learning models can enhance decision-making in spine surgery.
Takeaway
This article talks about how computers can help doctors make safer choices during surgery by predicting problems before they happen.
Digital Object Identifier (DOI)
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