Results 211 to 220 of about 425,037 (266)

Bayesian inverse ensemble forecasting for COVID‐19

Canadian Journal of Statistics, EarlyView.
Abstract Variations in strains of COVID‐19 have a significant impact on the rate of surges and on the accuracy of forecasts of the epidemic dynamics. The primary goal for this article is to quantify the effects of varying strains of COVID‐19 on ensemble forecasts of individual “surges.” By modelling the disease dynamics with an SIR model, we solve the ...
Kimberly Kroetch, Don Estep
wiley   +1 more source

Bayesian Inference of Pathogen Phylogeography using the Structured Coalescent Model. [PDF]

PLoS Comput Biol
Roberts I, Everitt RG, Koskela J, Didelot X.   +3 more
europepmc   +1 more source

A partial envelope approach for modelling multivariate spatial‐temporal data

Canadian Journal of Statistics, EarlyView.
Abstract In the new era of big data, modelling multivariate spatial‐temporal data is a challenging task due to both the high dimensionality of the features and complex associations among the responses across different locations and time points.
Reisa Widjaja, Wenbo Wu, Victor De Oliveira, Keying Ye   +3 more
wiley   +1 more source

Optimal Dose and Safety of Intravenous Favipiravir in Hospitalized Patients With COVID‐19: A Dose‐Escalating, Randomized Controlled Phase Ib Study

Clinical Pharmacology &Therapeutics, EarlyView.
AGILE (NCT04746183) is a Phase Ib/IIa platform, evaluating candidates to treat COVID‐19. Candidate Specific Trial 6 evaluated the safety and optimal dose of a novel intravenous formulation of favipiravir in a dose‐escalating, open‐label, randomized, controlled, Bayesian adaptive Phase Ib trial.
Tim Rowland, Richard FitzGerald, Elizabeth Challenger, Laura Dickinson, Laura J. Else, Lauren Walker, Colin Hale, Victoria Shaw, Callum Kelly, Rebecca Lyon, Jennifer Gibney, Karim Dhamani, Margaret Irwin, Yvanne Enever, Michelle Tetlow, William Wood, Helen Reynolds, Justin Chiong, Orod Osanlou, Henry Pertinez, Katie Bullock, William Greenhalf, Andrew Owen, David G. Lalloo, Michael Jacobs, Julian A. Hiscox, Thomas Jaki, Pavel Mozgunov, Geoffrey Saunders, Gareth Griffiths, Saye H. Khoo, Thomas E. Fletcher, on behalf of the AGILE CST‐6 Study Group, Shazaad Ahmad, Christopher J. Edwards, Lesley Dry, Georgie McKenzie, Aleksandra Ros, Michael Stackpoole, Laura Bradley, Karen Jennings‐Wilding, Nicholas Paton, Fred Hayden, Janet Darbyshire, Amy Lucas, Ulrika Lorch, Andrew Freedman, Richard Knight, Steven Julious   +48 more
wiley   +1 more source

A leptin-based Bayesian inference of a pro-satiety state reflects a basal circadian rhythm in women with obesity. [PDF]

Front Endocrinol (Lausanne)
Xiang Q, Khazaei S, Faghih RT.
europepmc   +1 more source

Bayesian inference for generalized linear models via quasi-posteriors. [PDF]

Biometrika
Agnoletto D, Rigon T, Dunson DB.
europepmc   +1 more source

Bayesian Inference for Drug Discovery by High Negative Samples and Oversampling. [PDF]

Bioinform Biol Insights
Le MH, Dao NA, Dang XT.
europepmc   +1 more source

Changes in facial expressions can distinguish Parkinson's disease via Bayesian inference. [PDF]

Front Neurol
Mouse M, Gong H, Liu Y, Xu F, Zou X, Huang M, Yang X.   +6 more
europepmc   +1 more source

Bayesian Inference of Phylogenetic Distances: Revisiting the Eigenvalue Approach. [PDF]

Bull Math Biol
Penn MJ, Scheidwasser N, Donnelly CA, Duchêne DA, Bhatt S.   +4 more
europepmc   +1 more source

Bayesian inference informed by parameter subset selection for a minimal PBPK brain model. [PDF]

Philos Trans A Math Phys Eng Sci
Dadashova K, Smith RC, Haider MA, Reich BJ.   +3 more
europepmc   +1 more source