Original paper
Artifacts annotations in anesthesia blood pressure data by man and machine
Volume: 35, Issue: 2, Pages: 259 - 267
Published: Aug 12, 2020
Abstract
Physiologic data from anesthesia monitors are automatically captured. Yet erroneous data are stored in the process as well. While this is not interfering with clinical care, research can be affected. Researchers should find ways to remove artifacts. The aim of the present study was to compare different artifact annotation strategies, and to assess if a machine learning algorithm is able to accept or reject individual data points. Non-cardiac...
Paper Details
Title
Artifacts annotations in anesthesia blood pressure data by man and machine
Published Date
Aug 12, 2020
Volume
35
Issue
2
Pages
259 - 267
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