CPT: pharmacometrics & systems pharmacology
Jun 14, 2024
We address the problem of model misspecification in population pharmacokinetics (PopPK), by modeling residual unexplained variability (RUV) by machine learning (ML) methods in a postprocessing step after conventional model building. The practical pur...
Swarm robots are frequently preferred for the exploration of harsh environments and search and rescue operations. This study explores the factors that influence the movement strategies of autonomous robot swarms and their impact on swarm distribution...
British journal of clinical pharmacology
Jun 11, 2024
AIMS: This study evaluated the use of machine learning to leverage drug absorption, distribution, metabolism and excretion (ADME) data together with physicochemical and pharmacological data to develop a novel anticholinergic burden scale and compare ...
A significant challenge in the traditional human health risk assessment of agrochemicals is the uncertainty in quantifying the interspecies differences between animal models and humans. To work toward a more accurate and animal-free risk determinatio...
British journal of clinical pharmacology
Jun 6, 2024
AIMS: Although there are various model-based approaches to individualized vancomycin (VCM) administration, few have been reported for adult patients with periprosthetic joint infection (PJI). This work attempted to develop a machine learning (ML)-bas...
Physics-based modeling methods have the potential to investigate the mechanical factors associated with knee osteoarthritis (OA) and predict the future radiographic condition of the joint. However, it remains unclear what level of detail is optimal i...
This study aims to investigate the feasibility of using an artificial lateral line (ALL) system for predicting the real-time position and pose of an undulating swimmer with Carangiform swimming patterns. We established a 3D computational fluid dynami...
Multi-factor screenings are commonly used in diverse applications in medicine and bioengineering, including optimizing combination drug treatments and microbiome engineering. Despite the advances in high-throughput technologies, large-scale experimen...
Preventative strategies and surgical treatments for urolithiasis depend on stone composition. However, stone composition is often unknown until the stone is passed or surgically managed. Given that stone composition likely reflects the physiological...
Stepwise covariate modeling (SCM) has a high computational burden and can select the wrong covariates. Machine learning (ML) has been proposed as a screening tool to improve the efficiency of covariate selection, but little is known about how to appl...