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Continuous Glucose Monitoring Time Series Data Analysis: A Time Series Analysis Package for Continuous Glucose Monitoring Data.

Jian ShaoZiqing LiuShaoyun LiBenrui WuZedong NieYuefei LiKaixin Zhou
Published in: Journal of computational biology : a journal of computational molecular cell biology (2022)
The R package Continuous Glucose Monitoring Time Series Data Analysis (CGMTSA) was developed to facilitate investigations that examine the continuous glucose monitoring (CGM) data as a time series. Accordingly, novel time series functions were introduced to (1) enable more accurate missing data imputation and outlier identification; (2) calculate recommended CGM metrics as well as key time series parameters; (3) plot interactive and three-dimensional graphs that allow direct visualizations of temporal CGM data and time series model optimization. The software was designed to accommodate all popular CGM devices and support all common data processing steps. The program is available for Linux, Windows, and Mac at GitHub.
Keyphrases
  • data analysis
  • electronic health record
  • big data
  • machine learning
  • mass spectrometry