Results 191 to 200 of about 404,944 (276)

Prevalence Estimation Methods for Time-Dependent Antibody Kinetics of Infected and Vaccinated Individuals: A Markov Chain Approach. [PDF]

Bull Math Biol
Bedekar P, Luke RA, Kearsley AJ.
europepmc   +1 more source

Semi‐mechanistic population PK/PD model to aid clinical understanding of myelodysplastic syndromes following treatment with Venetoclax and Azacitidine

CPT: Pharmacometrics &Systems Pharmacology, Volume 14, Issue 3, Page 448-459, March 2025.
Abstract Myelodysplastic syndromes (MDS) represent a group of bone marrow disorders involving cytopenias, hypercellular bone marrow, and dysplastic hematopoietic progenitors. MDS remains a challenge to treat due to the complex interplay between disease‐induced and treatment‐related cytopenias.
Neha Thakre, Corinna Maier, Jiuhong Zha, Benjamin Engelhardt, Johannes E. Wolff, Sven Mensing   +5 more
wiley   +1 more source

Improving predictions of rock tunnel squeezing with ensemble Q-learning and online Markov chain. [PDF]

Sci Rep
Fard HS, Parvin H, Mahmoudi M.
europepmc   +1 more source

Accelerating virtual patient generation with a Bayesian optimization and machine learning surrogate model

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

Identifiability and convergence behavior for Markov chain Monte Carlo using multivariate probit models. [PDF]

Commun Stat Theory Methods
Zhang X.
europepmc   +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, Anne Auperin, Jôel Guigay, Sébastien Salas, Sebastien Benzekry   +4 more
wiley   +1 more source

Rice Growth Estimation and Yield Prediction by Combining the DSSAT Model and Remote Sensing Data Using the Monte Carlo Markov Chain Technique. [PDF]

Plants (Basel)
Chen Y, Wang S, Xue Z, Hu J, Chen S, Lv Z.   +5 more
europepmc   +1 more source

Derived Markov Chains. II

Indagationes Mathematicae (Proceedings), 1962
openaire   +1 more source

Impact of Packaging and Recycling Systems on Material Recirculation: A Stage‐Decomposition Model

Packaging Technology and Science, EarlyView.
A system‐level view emerges from decomposing recycling into four stages (participation, collection, sorting and process yield), diagnosing constraints and targeting interventions. Cumulative equivalent uses (CEUs) quantify long‐term retention, revealing marginal improvements at high baselines generate disproportionately larger gains than low‐baseline ...
Diogo Figueirinhas, Daniel Hellström, Henrik Pålsson, Yulia Vakulenko   +3 more
wiley   +1 more source

An objective Bayesian method for including parameter uncertainty in ensemble model output statistics

Quarterly Journal of the Royal Meteorological Society, EarlyView.
Conventional model output statistics and ensemble model output statistics methods for calibrating ensemble forecasts lead to severe underestimation of the probabilities of ensemble extremes (in blue). This is because they ignore statistical parameter uncertainty.
Stephen Jewson, Leonardo Olivetti, Gabriele Messori, Paul J. Northrop, Trevor Sweeting   +4 more
wiley   +1 more source