Empirical study on artifact detection in monitoring data
C Cao, N McIntosh - Proceedings of the AMIA Symposium, 1998 - ncbi.nlm.nih.gov
C Cao, N McIntosh
Proceedings of the AMIA Symposium, 1998•ncbi.nlm.nih.govArtifacts in clinical monitoring are a serious problem, not just because they frustrate clinical
staff, but also because they prevent computer researchers from easily exploring and
exploiting the monitoring data. The best way of detecting artifacts still remains a
controversial issue. In this paper, we present a simple and practical method for identifying
monitoring artifacts. Experiments show that the method can detect most artifacts in 7 data
sets of different preterm infants with very low birth weight.
staff, but also because they prevent computer researchers from easily exploring and
exploiting the monitoring data. The best way of detecting artifacts still remains a
controversial issue. In this paper, we present a simple and practical method for identifying
monitoring artifacts. Experiments show that the method can detect most artifacts in 7 data
sets of different preterm infants with very low birth weight.
Abstract
Artifacts in clinical monitoring are a serious problem, not just because they frustrate clinical staff, but also because they prevent computer researchers from easily exploring and exploiting the monitoring data. The best way of detecting artifacts still remains a controversial issue. In this paper, we present a simple and practical method for identifying monitoring artifacts. Experiments show that the method can detect most artifacts in 7 data sets of different preterm infants with very low birth weight.
ncbi.nlm.nih.gov
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