Cargando…
Comparison of parametric and non‐parametric Bayesian inference for fusing sensory estimates in physiological time‐series analysis
The rapid proliferation of wearable devices for medical applications has necessitated the need for automated algorithms to provide labelling of physiological time‐series data to identify abnormal morphology. However, such algorithms are less reliable than gold‐standard human expert labels (where the...
Autores principales: | Zhu, Tingting, Javed, Hamza, Clifton, David A. |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley and Sons Inc.
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8024027/ https://www.ncbi.nlm.nih.gov/pubmed/33850626 http://dx.doi.org/10.1049/htl2.12003 |
Ejemplares similares
-
Parametric and non-parametric gradient matching for network inference: a comparison
por: Dony, Leander, et al.
Publicado: (2019) -
Spectral Decompositions of Multiple Time Series: A Bayesian Non-parametric Approach
por: Macaro, Christian, et al.
Publicado: (2013) -
Specifying statistical models: from parametric to non-parametric, using Bayesian or non-Bayesian approaches
por: Florens, J, et al.
Publicado: (1983) -
Parametric statistical inference
por: Lindsey, James K.
Publicado: (1996) -
hiHMM: Bayesian non-parametric joint inference of chromatin state maps
por: Sohn, Kyung-Ah, et al.
Publicado: (2015)