8 citations · 17 across the 13 of their papers we have counts for
14 papers
Learning to Detect Shifts in Unstructured Data Streams via Monitoring-by-Betting
Siyu Zhou, Jialin Ouyang, Fan Xia +8
Continuous monitoring of generative AI systems requires detecting distribution shifts in the unstructured data they ingest and generate. Existing monitoring methods typically contr…
Expert-Guided g-computation with Large Language Models for Estimating Causal Effects on Timings: Applications to Hospital Quality Improvement
Patrick Vossler, Jialin Ouyang, F. Richard Guo +5
Hospital quality improvement (QI) programs routinely face multiple candidate interventions to optimize hospital flow, but existing methods struggle to estimate and rank the causal…
Expert Evaluation of Clinical AI Tools on Real Point-of-Care Clinical Queries
Jean Feng, Vishal Patel, Patrick Heagerty +5
Physicians now pose millions of clinical questions to AI tools each week, yet these tools are evaluated largely on hypothetical or exam-style questions, not those actually asked in…
Adaptive auditing of AI systems with anytime-valid guarantees
Siyu Zhou, Patrick Vossler, Venkatesh Sivaraman +2
A major bottleneck in characterizing the failure modes of generative AI systems is the cost and time of annotation and evaluation. Consequently, adaptive testing paradigms have gai…
From Fuzzy to Formal: Scaling Hospital Quality Improvement with AI
Patrick Vossler, Jean Feng, Venkat Sivaraman +9
Hospital Quality Improvement (QI) plays a critical role in optimizing healthcare delivery by translating high-level hospital goals into actionable solutions. A critical step of QI…
More Than "Means to an End": Supporting Reasoning with Transparently Designed AI Data Science Processes
Venkatesh Sivaraman, Patrick Vossler, Adam Perer +2
Generative artificial intelligence (AI) tools can now help people perform complex data science tasks regardless of their expertise. While these tools have great potential to help m…
Human-AI Co-design for Clinical Prediction Models
Jean Feng, Avni Kothari, Patrick Vossler +6
Developing safe, effective, and practically useful clinical prediction models (CPMs) traditionally requires iterative collaboration between clinical experts, data scientists, and i…
When the Domain Expert Has No Time and the LLM Developer Has No Clinical Expertise: Real-World Lessons from LLM Co-Design in a Safety-Net Hospital
Avni Kothari, Patrick Vossler, Jean Digitale +8
Large language models (LLMs) have the potential to address social and behavioral determinants of health by transforming labor intensive workflows in resource-constrained settings.…
LLMs Judging LLMs: A Simplex Perspective
Patrick Vossler, Fan Xia, Yifan Mai +2
Given the challenge of automatically evaluating free-form outputs from large language models (LLMs), an increasingly common solution is to use LLMs themselves as the judging mechan…
ODTlearn: A Package for Learning Optimal Decision Trees for Prediction and Prescription
Patrick Vossler, Nathan Justin, Sina Aghaei +3
ODTlearn is an open source Python package that provides methods for learning optimal decision trees for high-stakes predictive and prescriptive tasks based on the state-of-the-art…
Deploying a Robust Active Preference Elicitation Algorithm on MTurk: Experiment Design, Interface, and Evaluation for COVID-19 Patient Prioritization
Caroline M. Johnston, Patrick Vossler, Simon Blessenohl +1
Preference elicitation leverages AI or optimization to learn stakeholder preferences in settings ranging from marketing to public policy. The online robust preference elicitation p…
Dimension-Free Average Treatment Effect Inference with Deep Neural Networks
Xinze Du, Yingying Fan, Jinchi Lv +2
This paper investigates the estimation and inference of the average treatment effect (ATE) using deep neural networks (DNNs) in the potential outcomes framework. Under some regular…
Asymptotic Properties of High-Dimensional Random Forests
Chien-Ming Chi, Patrick Vossler, Yingying Fan +1
As a flexible nonparametric learning tool, the random forests algorithm has been widely applied to various real applications with appealing empirical performance, even in the prese…
Optimal Nonparametric Inference with Two-Scale Distributional Nearest Neighbors
Emre Demirkaya, Yingying Fan, Lan Gao +3
The weighted nearest neighbors (WNN) estimator has been popularly used as a flexible and easy-to-implement nonparametric tool for mean regression estimation. The bagging technique…