Artificial intelligence model predicting postoperative pain using facial expressions: a pilot study
Author:
Publisher
Springer Science and Business Media LLC
Subject
Anesthesiology and Pain Medicine,Critical Care and Intensive Care Medicine,Health Informatics,Anesthesiology and Pain Medicine,Critical Care and Intensive Care Medicine,Health Informatics
Link
https://link.springer.com/content/pdf/10.1007/s10877-023-01100-7.pdf
Reference29 articles.
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2. Gan TJ, Habib AS, Miller TE, White W, Apfelbaum JL. Incidence, patient satisfaction, and perceptions of post-surgical pain: results from a US national survey. Curr Med Res Opin. 2014;30:149–60. https://doi.org/10.1185/03007995.2013.860019.
3. Kehlet H, Jensen TS, Woolf CJ. Persistent postsurgical pain: risk factors and prevention. Lancet. 2006;367:1618–25. https://doi.org/10.1016/s0140-6736(06)68700-x.
4. Bijur PE, Latimer CT, Gallagher EJ. Validation of a verbally administered numerical rating scale of acute pain for use in the emergency department. Acad Emerg Med. 2003;10:390–2. https://doi.org/10.1111/j.1553-2712.2003.tb01355.x.
5. Bahreini M, Jalili M, Moradi-Lakeh M. A comparison of three self-report pain scales in adults with acute pain. J Emerg Med. 2015;48:10–8. https://doi.org/10.1016/j.jemermed.2014.07.039.
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