Machine learning and decision support in critical care
Clinical data management systems typically provide caregiver teams with useful information,
derived from large, sometimes highly heterogeneous, data sources that are often changing …
derived from large, sometimes highly heterogeneous, data sources that are often changing …
Alarm algorithms in critical care monitoring
M Imhoff, S Kuhls - Anesthesia & Analgesia, 2006 - journals.lww.com
The alarms of medical devices are a matter of concern in critical and perioperative care. The
frequent false alarms not only are a nuisance for patients and caregivers but can also …
frequent false alarms not only are a nuisance for patients and caregivers but can also …
A network approach to psychopathology: new insights into clinical longitudinal data
In the network approach to psychopathology, disorders are conceptualized as networks of
mutually interacting symptoms (eg, depressed mood) and transdiagnostic factors (eg …
mutually interacting symptoms (eg, depressed mood) and transdiagnostic factors (eg …
A temporal comparison of BOLD, ASL, and NIRS hemodynamic responses to motor stimuli in adult humans
In this study, we have preformed simultaneous near-infrared spectroscopy (NIRS) along with
BOLD (blood oxygen level dependent) and ASL (arterial spin labeling)-based fMRI during …
BOLD (blood oxygen level dependent) and ASL (arterial spin labeling)-based fMRI during …
A data imputation method for multivariate time series based on generative adversarial network
Multivariate time series (MTS) processing plays an important role in many fields such as
industry, finance, medical, etc. However, the presence of missing data in MTS makes data …
industry, finance, medical, etc. However, the presence of missing data in MTS makes data …
Bayesian statistics in medicine: a 25 year review
D Ashby - Statistics in medicine, 2006 - Wiley Online Library
This review examines the state of Bayesian thinking as Statistics in Medicine was launched
in 1982, reflecting particularly on its applicability and uses in medical research. It then looks …
in 1982, reflecting particularly on its applicability and uses in medical research. It then looks …
Causality and graphical models in time series analysis
R Dahlhaus, M Eichler - Oxford Statistical Science Series, 2003 - books.google.com
Over the last few years there has been growing interest in graphical models and in particular
in those based on directed acyclic graphs as a general framework to describe and infer …
in those based on directed acyclic graphs as a general framework to describe and infer …
A graphical vector autoregressive modelling approach to the analysis of electronic diary data
Background In recent years, electronic diaries are increasingly used in medical research
and practice to investigate patients' processes and fluctuations in symptoms over time. To …
and practice to investigate patients' processes and fluctuations in symptoms over time. To …
Sparse multi-output Gaussian processes for online medical time series prediction
Background For real-time monitoring of hospital patients, high-quality inference of patients'
health status using all information available from clinical covariates and lab test results is …
health status using all information available from clinical covariates and lab test results is …
Convergence of covariance and spectral density estimates for high-dimensional locally stationary processes
D Zhang, WB Wu - 2021 - projecteuclid.org
Convergence of covariance and spectral density estimates for high-dimensional locally
stationary processes Page 1 The Annals of Statistics 2021, Vol. 49, No. 1, 233–254 https://doi.org/10.1214/20-AOS1954 …
stationary processes Page 1 The Annals of Statistics 2021, Vol. 49, No. 1, 233–254 https://doi.org/10.1214/20-AOS1954 …