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个体化处理效应预测的评价：区分度与校准的模型视角AI 解读

In recent years, there has been a growing interest in the prediction of individualized treatment effects. While there is a rapidly growing literature on the development of such models, there is little literature on the evaluation of their performance. In this paper, we aim to facilitate the validation of prediction models for individualized treatment effects. The estimands of interest are defined as based on the potential outcomes framework, which facilitates a comparison of…

随机试验中二元结局个体化处理效应预测教程AI 解读

Randomized trials typically estimate average relative treatment effects, but decisions on the benefit of a treatment are possibly better informed by more individualized predictions of the absolute treatment effect. In case of a binary outcome, these predictions of absolute individualized treatment effect require knowledge of the individual's risk without treatment and incorporation of a possibly differential treatment effect (i.e. varying with patient characteristics). In…