5 papers
The CRITICAL Records Integrated Standardization Pipeline (CRISP): End-to-End Processing of Large-scale Multi-institutional OMOP CDM Data
Xiaolong Luo, Michael Lingzhi Li
While existing critical care EHR datasets such as MIMIC and eICU have enabled significant advances in clinical AI research, the CRITICAL dataset opens new frontiers by providing ex…
Statistical Performance Guarantee for Subgroup Identification with Generic Machine Learning
Michael Lingzhi Li, Kosuke Imai
Across a wide array of disciplines, many researchers use machine learning (ML) algorithms to identify a subgroup of individuals who are likely to benefit from a treatment the most…
Balancing Optimality and Diversity: Human-Centered Decision Making through Generative Curation
Michael Lingzhi Li, Shixiang Zhu
Many decision-support systems recommend actions by optimizing measurable objectives, even when a human decision-maker retains final authority and considers additional criteria that…
Cramming Contextual Bandits for On-policy Statistical Evaluation
Zeyang Jia, Kosuke Imai, Michael Lingzhi Li
We introduce the cram method as a general statistical framework for evaluating the final learned policy from a multi-armed contextual bandit algorithm, using the dataset generated…
Comment on "Generic machine learning inference on heterogeneous treatment effects in randomized experiments."
Kosuke Imai, Michael Lingzhi Li
We analyze the split-sample robust inference (SSRI) methodology proposed by Chernozhukov, Demirer, Duflo, and Fernandez-Val (CDDF) for quantifying uncertainty in heterogeneous trea…