An independent central point OPTICS clustering algorithm for semi-supervised outlier detection of continuous glucose measurements

Volume: 71, Pages: 103196 - 103196
Published: Jan 1, 2022
Abstract
Continuous glucose monitoring (CGM) collects a host of time-series sensor data and is committed to fully automated systems for glucose control as an essential part. Outlier data in CGM measurements caused by faults may seriously affect the computation of insulin infusion rates and endanger the safety of patients. In this paper, a semi-supervised outlier detection method is proposed for anomaly detection of glucose concentration measurements...
Paper Details
Title
An independent central point OPTICS clustering algorithm for semi-supervised outlier detection of continuous glucose measurements
Published Date
Jan 1, 2022
Volume
71
Pages
103196 - 103196
Citation AnalysisPro
  • Scinapse’s Top 10 Citation Journals & Affiliations graph reveals the quality and authenticity of citations received by a paper.
  • Discover whether citations have been inflated due to self-citations, or if citations include institutional bias.