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Predicting vital sign deviations during surgery from patient monitoring data: developing and validating single-stream

Alina Dubatovka1, Christoph B Nöthiger2, Donat R Spahn2

  • 1Department of Computer Science, ETH Zurich, Zurich, Switzerland.

British Journal of Anaesthesia
|August 1, 2024
PubMed
Summary

No abstract available in PubMed .

Keywords:
algorithmsartificial intelligencebiosignalsclinical decision support systemsdigital medicinemachine learningperioperative medicine, vital signs

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Vital signs are physiological measurements that help key into the status of the body's essential functions. These include body temperature, pulse rate, respiratory rate, and blood pressure, commonly abbreviated as T, P, R, and BP. Some healthcare settings also consider oxygen saturation (SpO2) and, in specific contexts, pain and level of consciousness as additional vital signs.
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Following these guidelines can help nurses accurately measure vital signs, assess changes in patient conditions, and provide timely treatment when necessary. Adhering closely to the guidelines ensures the accuracy and reliability of the results.
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