Cargando…
Using generalized additive models to decompose time series and waveforms, and dissect heart–lung interaction physiology
Common physiological time series and waveforms are composed of repeating cardiac and respiratory cycles. Often, the cardiac effect is the primary interest, but for, e.g., fluid responsiveness prediction, the respiratory effect on arterial blood pressure also convey important information. In either c...
Autores principales: | Enevoldsen, Johannes, Simpson, Gavin L., Vistisen, Simon T. |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer Netherlands
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9852126/ https://www.ncbi.nlm.nih.gov/pubmed/35695942 http://dx.doi.org/10.1007/s10877-022-00873-7 |
Ejemplares similares
-
Gastrointestinal transit time and heart rate variability in patients with mild acquired brain injury
por: Enevoldsen, Johannes, et al.
Publicado: (2018) -
Prevalence and Temporal Distribution of Extrasystoles in Septic ICU Patients: The Feasibility of Predicting Fluid Responsiveness Using Extrasystoles
por: Enevoldsen, Johannes, et al.
Publicado: (2018) -
Flow pumping system for physiological waveforms
por: Tsai, William, et al.
Publicado: (2010) -
Physiology and clinical utility of the peripheral venous waveform
por: Chang, Devin, et al.
Publicado: (2020) -
DRCNN: decomposing residual convolutional neural networks for time series forecasting
por: Zhu, Yuzhen, et al.
Publicado: (2023)