Chaotic time series prediction for glucose dynamics in type 1 diabetes mellitus using regime-switching models
Abstract In patients with type 1 diabetes mellitus (T1DM), glucose dynamics are influenced by insulin reactions, diet, lifestyle, etc., and characterized by instability and nonlinearity. With the objective of a dependable decision support system for T1DM self-management, we aim to model glucose dyna...
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| Auteurs principaux: | , , , |
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| Format: | article |
| Langue: | EN |
| Publié: |
Nature Portfolio
2017
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| Accès en ligne: | https://doaj.org/article/b60fa2131072410cbb72e6a125e9f550 |
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