Pharmacokinetic Models: Comparison and Selection Criterion
Multi-input and Multi-variable systems
Survival Tree
One-Compartment Open Model: Wagner-Nelson and Loo Riegelman Method for ka Estimation
Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving
Woodward–Hoffmann Selection Rules and Microscopic Reversibility
You might also read
Articles linked to this work by shared authors, journal, and citation graph.
Updated: Sep 26, 2025

A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
Published on: January 11, 2020
Viet Hung Dao1, David Gunawan2, Minh-Ngoc Tran2
1School of Economics, University of New South Wales.
We developed a new computational method, cross-validation via variational Bayes (CVVB), to efficiently compare complex psychological models. CVVB makes advanced model comparison techniques accessible for hierarchical cognitive models, saving significant computational time.
Area of Science:
Background:
Purpose of the Study:
Main Methods:
Main Results:
Conclusions: