Personalised patient monitoring in haemodialysis using hierarchical Gaussian processes
The prevalence of end-stage renal failure is 861 per million population in the UK, and these patients undergo three haemodialysis sessions per week, each lasting 4 hours. In addition, patients are at risk of intra-dialytic hypotension, which leads to chronic heart disease and a high incidence of mor...
Hauptverfasser: | Zhu, T, Colopy, G, Pugh, C, Clifton, D |
---|---|
Format: | Conference item |
Veröffentlicht: |
Institute of Electrical and Electronics Engineers
2017
|
Ähnliche Einträge
Ähnliche Einträge
-
Patient-specific physiological monitoring and prediction using structured Gaussian processes
von: Zhu, T, et al.
Veröffentlicht: (2019) -
Bayesian optimisation of personalised models for patient vital-sign monitoring
von: Colopy, GW, et al.
Veröffentlicht: (2017) -
Bayesian Gaussian processes for identifying the deteriorating patient
von: Colopy, G, et al.
Veröffentlicht: (2016) -
State-space approximations to Gaussian processes for patient vital-sign monitoring in computationally-constrained clinical environments
von: Colopy, G, et al.
Veröffentlicht: (2016) -
Bayesian optimisation of Gaussian processes for identifying the deteriorating patient
von: Colopy, G, et al.
Veröffentlicht: (2017)