Results 131 to 140 of about 85,479 (297)
CPT: Pharmacometrics &Systems Pharmacology, Volume 14, Issue 3, Page 486-494, March 2025.Abstract The pharmaceutical industry has increasingly adopted model‐informed drug discovery and development (MID3) to enhance productivity in drug discovery and development. Quantitative systems pharmacology (QSP), which integrates drug action mechanisms and disease complexities to predict clinical endpoints and biomarkers is central to MID3.
Hiroaki Iwata, Ryuta Saito
wiley +1 more source
Revista Colombiana de Estadística, 2011 In this paper, we introduce a Bayesian analysis for survival multivariate data in the presence of a covariate vector and censored observations. Different "frailties" or latent variables are considered to capture the correlation among the survival times ...
JORGE ALBERTO ACHCAR +1 more
doaj
Practical guidelines for Bayesian phylogenetic inference using Markov chain Monte Carlo (MCMC). [PDF]
Open Res Eur, 2023 Barido-Sottani J +4 more
europepmc +1 more source
Using Kansas Farm data from 1973 to 1998, curvature restrictions are imposed on a translog cost function. Using uninformative priors with indicator functions representing distribution and inequality constraints, a Markov Chain Monte Carlo Simulation ...
Featherstone, Allen M. +2 more
core
Parallel Markov Chain Monte Carlo [PDF]
The increasing availability of multi-core and multi-processor architectures provides\ud new opportunities for improving the performance of many computer simulations.\ud Markov Chain Monte Carlo (MCMC) simulations are widely used for approximate\ud counting problems, Bayesian inference and as a means for estimating very highdimensional\ud integrals.
openaire +1 more source
Mechanistic Learning for Predicting Survival Outcomes in Head and Neck Squamous Cell Carcinoma
CPT: Pharmacometrics &Systems Pharmacology, Volume 14, Issue 3, Page 540-550, March 2025.ABSTRACT We employed a mechanistic learning approach, integrating on‐treatment tumor kinetics (TK) modeling with various machine learning (ML) models to address the challenge of predicting post‐progression survival (PPS)—the duration from the time of documented disease progression to death—and overall survival (OS) in Head and Neck Squamous Cell ...
Kevin Atsou +4 more
wiley +1 more source
Ideal-Observer Computation with anthropomorphic phantoms using Markov chain Monte Carlo. [PDF]
Proc IEEE Int Symp Biomed Imaging, 2022 Rahman MA, Yu Z, Jha AK.
europepmc +1 more source
Bivariate postprocessing of wind vectors
Quarterly Journal of the Royal Meteorological Society, EarlyView.We introduce three novel bivariate postprocessing approaches and analyze their performance for joint postprocessing of bivariate wind‐vector components in Germany. Bivariate vine‐copula‐based models, a bivariate gradient‐boosted version of ensemble model output statistics (EMOS), and a bivariate distributional regression network (DRN) are compared with
Ferdinand Buchner +3 more
wiley +1 more source
A Markov Chain Monte Carlo Multiple Imputation Procedure for Dealing with Item Nonresponse in the German SAVE Survey [PDF]
Important empirical information on household behavior is obtained from surveys. However, various interdependent factors that can only be controlled to a limited extent lead to unit and item nonresponse, and missing data on certain items is a frequent ...
Schunk, Daniel
core +2 more sources
Use of the reversible jump Markov chain Monte Carlo algorithm to select multiplicative terms in the AMMI-Bayesian model. [PDF]
PLoS One, 2023 Silva CPD +5 more
europepmc +1 more source