Automated anesthesia artifact analysis: can machines be trained to take out the garbage?

Allan F Simpao^{1

2}, Olivia Nelson^{3

4}, Luis M Ahumada^{5

6}

Affiliations

¹ Department of Anesthesiology and Critical Care Medicine, Children's Hospital of Philadelphia, 3401 Civic Center Blvd, Philadelphia, PA, 19104-4399, USA. simpaoa@email.chop.edu.
² Department of Anesthesiology and Critical Care, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, 19104, USA. simpaoa@email.chop.edu.
³ Department of Anesthesiology and Critical Care Medicine, Children's Hospital of Philadelphia, 3401 Civic Center Blvd, Philadelphia, PA, 19104-4399, USA.
⁴ Department of Anesthesiology and Critical Care, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, 19104, USA.
⁵ Department of Health Informatics, Predictive Analytics Core, Johns Hopkins All Children's Hospital, 501 6th Ave S, St. Petersburg, FL, 33701, USA.
⁶ Department of Anesthesiology and Critical Care Medicine, Johns Hopkins School of Medicine, 733 N Broadway, Baltimore, MD, 21205, USA.

PMID: 32920701
DOI: 10.1007/s10877-020-00589-6

Comment

Automated anesthesia artifact analysis: can machines be trained to take out the garbage?

Allan F Simpao et al. J Clin Monit Comput. 2021 Apr.

. 2021 Apr;35(2):225-227.

doi: 10.1007/s10877-020-00589-6. Epub 2020 Sep 12.

Authors

Allan F Simpao^{1

2}, Olivia Nelson^{3

4}, Luis M Ahumada^{5

6}

Affiliations

¹ Department of Anesthesiology and Critical Care Medicine, Children's Hospital of Philadelphia, 3401 Civic Center Blvd, Philadelphia, PA, 19104-4399, USA. simpaoa@email.chop.edu.
² Department of Anesthesiology and Critical Care, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, 19104, USA. simpaoa@email.chop.edu.
³ Department of Anesthesiology and Critical Care Medicine, Children's Hospital of Philadelphia, 3401 Civic Center Blvd, Philadelphia, PA, 19104-4399, USA.
⁴ Department of Anesthesiology and Critical Care, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, 19104, USA.
⁵ Department of Health Informatics, Predictive Analytics Core, Johns Hopkins All Children's Hospital, 501 6th Ave S, St. Petersburg, FL, 33701, USA.
⁶ Department of Anesthesiology and Critical Care Medicine, Johns Hopkins School of Medicine, 733 N Broadway, Baltimore, MD, 21205, USA.

PMID: 32920701
DOI: 10.1007/s10877-020-00589-6

No abstract available

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Artifacts annotations in anesthesia blood pressure data by man and machine.
Pasma W, Wesselink EM, van Buuren S, de Graaff JC, van Klei WA. Pasma W, et al. J Clin Monit Comput. 2021 Apr;35(2):259-267. doi: 10.1007/s10877-020-00574-z. Epub 2020 Aug 12. J Clin Monit Comput. 2021. PMID: 32783094 Free PMC article.

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References

1. Simpao AF, Ahumada LM. Rehman MA Big data and visual analytics in anaesthesia and health care. Br J Anaesth. 2015;115:350–6. https://doi.org/10.1093/bja/aeu552 . - DOI - PubMed
1. Kilkenny MF, Robinson KM. Data quality: garbage in–garbage out. Health Inf Manag. 2018;47:103–5. https://doi.org/10.1177/1833358318774357 . - DOI - PubMed
1. Takla G, Petre JH, Doyle DJ, Horibe M, Gopakumaran B. The problem of artifacts in patient monitor data during surgery: a clinical and methodological review. Anesth Analg. 2006;103:1196–204. https://doi.org/10.1213/01.ane.0000247964.47706.5d . - DOI - PubMed
1. Eden A, Grach M, Goldik Z, et al. The implementation of an anesthesia information management system. Eur J Anaesthesiol. 2006;23:882–9. https://doi.org/10.1017/S0265021506000834 . - DOI - PubMed
1. Hravnak M, Chen L, Bose E, et al. Artifact patterns in continuous noninvasive monitoring of patients. Intensive Care Med. 2013;39:S405. - PubMed - PMC

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Automated anesthesia artifact analysis: can machines be trained to take out the garbage?

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