Visualizing Multivariate Time Series Data to Detect Specific Medical Conditions

@article{Ordez2008VisualizingMT,
  title={Visualizing Multivariate Time Series Data to Detect Specific Medical Conditions},
  author={Patricia Ord{\'o}{\~n}ez and Marie desJardins and Carolyn Feltes and Christoph U. Lehmann and James C. Fackler},
  journal={AMIA ... Annual Symposium proceedings. AMIA Symposium},
  year={2008},
  pages={530-4}
}
Efficient unsupervised algorithms for the detection of patterns in time series data, often called motifs, have been used in many applications, such as identifying words in different languages, detecting anomalies in ECG readings, and finding similarities between images. We present a process that creates a personalized multivariate time series representation… CONTINUE READING