Classification of longitudinal profiles using semi-parametric nonlinear mixed models with P-Splines and the SAEM algorithm

Keyphrases

• Semi-parametric 100%
• Longitudinal Profile 100%
• NONMEM 100%
• SAEM Algorithm 100%
• P-splines 100%
• Penalized Splines 66%
• Change of Measure 33%
• Early Detection 33%
• Unified Framework 33%
• Variance Components 33%
• Importance Sampling 33%
• Health Outcomes 33%
• Maximum Likelihood 33%
• Longitudinal Data 33%
• Pregnant Women 33%
• Random Effects 33%
• EM Algorithm 33%
• Pregnancy Outcome 33%
• Stochastic Approximation 33%
• Mixed-effects Model 33%
• Early Monitoring 33%
• Maternal Health 33%
• During Pregnancy 33%
• Fetal Health 33%
• Supervised Classification Methods 33%
• Pregnancy Disorders 33%
• Adaptive Importance Sampling 33%

INIS

• algorithms 100%
• classification 100%
• nonlinear problems 100%
• pregnancy 75%
• data 50%
• women 50%
• proposals 50%
• comparative evaluations 25%
• information 25%
• detection 25%
• monitoring 25%
• randomness 25%
• sampling 25%
• indicators 25%
• flexibility 25%
• biological markers 25%
• maximum-likelihood fit 25%
• approximations 25%
• stochastic processes 25%
• computer codes 25%

Mathematics

• Parametric 100%
• Nonlinear Mixed Model 100%
• Spline 100%
• Maximum Likelihood 33%
• Stochastics 33%
• Importance Sampling 33%
• Pregnant Woman 33%
• Longitudinal Data 33%
• Random Effect 33%
• Variance Component 33%
• Classification Method 33%
• EM Algorithm 33%
• Sampling Scheme 33%