Automated anesthesia artifact analysis: can machines be trained to take out the garbage?
Author:
Publisher
Springer Science and Business Media LLC
Subject
Anesthesiology and Pain Medicine,Critical Care and Intensive Care Medicine,Health Informatics
Link
https://link.springer.com/content/pdf/10.1007/s10877-020-00589-6.pdf
Reference27 articles.
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2. Kilkenny MF, Robinson KM. Data quality: garbage in–garbage out. Health Inf Manag. 2018;47:103–5. https://doi.org/10.1177/1833358318774357.
3. 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.
4. 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.
5. Hravnak M, Chen L, Bose E, et al. Artifact patterns in continuous noninvasive monitoring of patients. Intensive Care Med. 2013;39:S405.
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