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Estimating Individualized Treatment Regimes to Optimize Incremental Cost-Effectiveness Ratio
Medical decision making can be challenging due to the trade-off between improving clinical efficacy and the associated medical costs. Evaluation of...
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Targeted Search for Individualized Clinical Decision Rules to Optimize Clinical Outcomes
Novel biomarkers, in combination with currently available clinical information, have been sought to enhance clinical decision making in many branches...
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Privacy-preserving estimation of an optimal individualized treatment rule: a case study in maximizing time to severe depression-related outcomes
Estimating individualized treatment rules—particularly in the context of right-censored outcomes—is challenging because the treatment effect...
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Estimating Heterogeneous Treatment Effect on Multivariate Responses Using Random Forests
Estimating the individualized treatment effect has become one of the most popular topics in statistics and machine learning communities in recent...
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A high-dimensional single-index regression for interactions between treatment and covariates
This paper explores a methodology for dimension reduction in regression models for a treatment outcome, specifically to capture covariates’...
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Bayesian Index Models for Heterogeneous Treatment Effects on a Binary Outcome
This paper develops a Bayesian model with a flexible link function connecting a binary treatment response to a linear combination of covariates and a...
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Personalized Medicine with Advanced Analytics
Practice of modern medicine demands personalized medicine (PM) to improve both quality of care and efficiency of the healthcare system. This is...
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Outcome Weighted Learning in Dynamic Treatment Regimes
This chapter discusses applications of information geometry in a paradigm of reinforcement learningReinforcement learning with emphasis on dynamic...
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Estimating the optimal treatment regime for student success programs
We expand methods for estimating an optimal treatment regime (OTR) from the personalized medicine literature to educational data mining applications....
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Sequential, Multiple Assignment, Randomized Trials (SMART)
A dynamic treatment regimen (DTR) is a prespecified set of decision rules that can be used to guide important clinical decisions about treatment...
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Logical Inference on Treatment Efficacy When Subgroups Exist
With rapid advances in understanding of human diseases, the paradigm of medicine shifts from “one-fits-all” to targeted therapies. In targeted...
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Sequential, Multiple Assignment, Randomized Trials (SMART)
A dynamic treatment regimen (DTR) is a prespecified set of decision rules that can be used to guide important clinical decisions about treatment...
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Targeted Learning of Optimal Individualized Treatment Rules Under Cost Constraints
We consider a general resource-allocationResource allocation problem, namely, to maximize a mean outcome given a cost constraintCost constraint,...
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Statistical Learning Methods for Optimizing Dynamic Treatment Regimes in Subgroup Identification
Many statistical learning methods have been developed to optimize multistage dynamic treatment regimes (DTRs) and identify subgroups that most...
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Causal Inference with Targeted Learning for Producing and Evaluating Real-World Evidence
Targeted Learning (TL) provides a unified framework for generating and evaluating real-world evidence (RWE) and thus can serve as a foundation for...
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Optimal Dynamic Treatment Rules
Suppose we observe n independent and identically distributed observations of a time-dependent random variable consisting of baseline covariates,...
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Using the discontinuation rule to reduce the effect of random guessing on parameter estimation in the item response theory
The discontinuation rule is often used to reduce the effect of random guessing in psychological tests. It may also play the similar role in the item...
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Small and negative correlations among clustered observations: limitations of the linear mixed effects model
The linear mixed effects model is an often used tool for the analysis of multilevel data. However, this model has an ill-understood shortcoming: it...
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Business Transformation Using Big Data Analytics and Machine Learning
Artificial intelligence (AI), big data, and business analytics are the most commonly used and complete common sense cognitive tools in the ecospheres...
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Optimal Individualized Treatments Under Limited Resources
In this chapter, we consider a resource constraint under which there is a maximum proportion of the population that can be treated. Given this...