Comparison of time series clustering methods for identifying novel subphenotypes of patients with infection.
Sign Up to like & getrecommendations! Published in 2023 at "Journal of the American Medical Informatics Association : JAMIA"
DOI: 10.1093/jamia/ocad063
Abstract: OBJECTIVE Severe infection can lead to organ dysfunction and sepsis. Identifying subphenotypes of infected patients is essential for personalized management. It is unknown how different time series clustering algorithms compare in identifying these subphenotypes. MATERIALS… read more here.
Keywords: time; time series; infection; group ... See more keywords
Efficient Time Series Clustering by Minimizing Dynamic Time Warping Utilization
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DOI: 10.1109/access.2021.3067833
Abstract: Dynamic Time Warping (DTW) is a widely used distance measurement in time series clustering. DTW distance is invariant to time series phase perturbations but has a quadratic complexity. An effective acceleration method must reduce the… read more here.
Keywords: series clustering; time; distance; time series ... See more keywords
Time-Series Clustering Based on the Characterization of Segment Typologies
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DOI: 10.1109/tcyb.2019.2962584
Abstract: Time-series clustering is the process of grouping time series with respect to their similarity or characteristics. Previous approaches usually combine a specific distance measure for time series and a standard clustering method. However, these approaches… read more here.
Keywords: series clustering; time; time series; clustering based ... See more keywords
Regional Economic Disparities in Europe: Time-Series Clustering of NUTS 3 Regions
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DOI: 10.1177/01600176221125703
Abstract: The aim of this research is to identify the regional economic disparities in the level of economic wealth and its dynamics in the NUTS 3 regions in EU28 over the period from 2000 to 2017.… read more here.
Keywords: nuts level; regional economic; time series; series clustering ... See more keywords
Clustering Macroeconomic Time Series
Sign Up to like & getrecommendations! Published in 2017 at "Econometrics"
DOI: 10.15611/eada.2018.2.06
Abstract: Abstract The data mining technique of time series clustering is well established. However, even when recognized as an unsupervised learning method, it does require making several design decisions that are nontrivially influenced by the nature… read more here.
Keywords: time series; time; series clustering; clustering macroeconomic ... See more keywords