Methods for subgroup identification / personalized medicine / individualized treatment rules
The package is developed for treatment recommendation & pairwise treatment individual effect estimation (ITE/CATE/HTE) when multiple treatment/intervention options exist. The package is still under development.
MultiMlearn - Estimation of individualized treatment rules using matched learning (M-learning), under the setting of multicategory treatments.
A maximum-likelihood-based deep learning method for estimating the conditional density, with an application to individualized treatment rule.
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