The landscape of medical treatments is undergoing a transformative shift. Precision
medicine has ushered in a revolutionary era in healthcare by individualizing diagnostics and …

Background: Therapeutic drug monitoring (TDM) and model-informed precision dosing
(MIPD) have greatly benefitted from computational and mathematical advances over the …

In recent years, the use of artificial intelligence (AI) in health care has risen steadily,
including a wide range of applications in the field of pharmacology. AI is now used …

Precision medicine requires individualized modeling of disease and drug dynamics, with
machine learning-based computational techniques gaining increasing popularity. The …

We previously demonstrated that Machine learning (ML) algorithms can accurately estimate
drug area under the curve (AUC) of tacrolimus or mycophenolate mofetil (MMF) based on …

Introduction Estimation of vancomycin area under the curve (AUC) is challenging in the case
of discontinuous administration. Machine learning approaches are increasingly used and …

The application of machine learning (ML) has shown promising results in precision medicine
due to its exceptional performance in dealing with complex multidimensional data. However …

Background As diagnostic and prognostic models developed by traditional statistics perform
poorly in real-world, artificial intelligence (AI) and Big Data (BD) may improve the supply …

Everolimus is an immunosuppressant with a small therapeutic index and large between‐
patient variability. The area under the concentration versus time curve (AUC) is the best …

Abstract Background Maximum a posteriori Bayesian estimation (MAP-BE) based on a
limited sampling strategy and a population pharmacokinetic model is frequently used to …