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本库首次提交范围:2004-06-23 — 2026-10-14。
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Using binary silver labels in electronic health records-based computable phenotyping algorithms

在电子健康记录表型算法中使用二元银标签

Gold-standard phenotype labels are often unavailable at scale in electronic health record (EHR) studies because they require manual chart review. Weakly supervised phenotyping methods instead use silver-standard labels, such as diagnosis-code counts, natural language processing (NLP) mentions, medication indicators, or laboratory thresholds. PheNorm is widely used for this purpose, but its original formulation was designed for count-valued silver labels and relies on log…

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Inference on summaries of a model-agnostic longitudinal variable importance trajectory with application to suicide prevention

模型无关的纵向变量重要性轨迹摘要推断及其自杀预防应用

Risk of suicide attempt varies over time. Understanding the importance of risk factors measured at a mental health visit can help clinicians evaluate future risk and provide appropriate care during the visit. In prediction settings where data are collected over time, such as in mental health care, it is often of interest to understand both the importance of variables for predicting the response at each time point and the importance summarized over the time series. Building…

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Assessing treatment effects in observational data with missing confounders: A comparative study of practical doubly-robust and traditional missing data methods

混杂变量缺失时的处理效应评估:双重稳健与传统缺失数据方法比较

In pharmacoepidemiology, safety and effectiveness are frequently evaluated using readily available administrative and electronic health records data. In these settings, detailed confounder data are often not available in all data sources and therefore missing on a subset of individuals. Multiple imputation (MI) and inverse-probability weighting (IPW) are go-to analytical methods to handle missing data and are dominant in the biomedical literature. Doubly-robust methods,…

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A cautionary note for plasmode simulation studies in the setting of causal inference

因果推断中 Plasmode 模拟研究的注意事项

Plasmode simulation has become an important tool for evaluating the operating characteristics of different statistical methods in complex settings, such as pharmacoepidemiological studies of treatment effectiveness using electronic health records (EHR) data. These studies provide insight into how estimator performance is impacted by challenges including rare events, small sample size, etc., that can indicate which among a set of methods performs best in a real-world dataset.…

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