323 citations
- University of California, BerkeleyUS4 papers
- Harvard UniversityUS2 papers
- Johns Hopkins UniversityUS2 papers
- Kaiser Permanente Washington Health Research InstituteUS2 papers
- University of California, San FranciscoUS2 papers
- University of WashingtonUS2 papers
- Ansan UniversityKR1 paper
- Beijing University of Posts and TelecommunicationsCN1 paper
- Brigham and Women's HospitalUS1 paper
- California NanoSystems InstituteUS1 paper
- Carnegie Mellon UniversityUS1 paper
- Columbia UniversityUS1 paper
16 papers
Multi-agent Self-triage System with Medical Flowcharts
Yujia Liu, Sophia Yu, Hongyue Jin +8
Online health resources and large language models (LLMs) are increasingly used as a first point of contact for medical decision-making, yet their reliability in healthcare remains…
Combining Insights From Multiple Large Language Models Improves Diagnostic Accuracy
Gioele Barabucci, Victor Shia, Eugene Chu +2
Background: Large language models (LLMs) such as OpenAI's GPT-4 or Google's PaLM 2 are proposed as viable diagnostic support tools or even spoken of as replacements for "curbside c…
A Probabilistic Method to Predict Classifier Accuracy on Larger Datasets given Small Pilot Data
Ethan Harvey, Wansu Chen, David M. Kent +1
Practitioners building classifiers often start with a smaller pilot dataset and plan to grow to larger data in the near future. Such projects need a toolkit for extrapolating how m…
Causal Quantile Treatment Effects with missing data by double-sampling
Shuo Sun, Sebastien Haneuse, Alexander W. Levis +5
Causal weighted quantile treatment effects (WQTE) are a useful complement to standard causal contrasts that focus on the mean when interest lies at the tails of the counterfactual…
Patient Clustering via Integrated Profiling of Clinical and Digital Data
Dongjin Choi, Andy Xiang, Ozgur Ozturk +5
We introduce a novel profile-based patient clustering model designed for clinical data in healthcare. By utilizing a method grounded on constrained low-rank approximation, our mode…
An Application of the Causal Roadmap in Two Safety Monitoring Case Studies: Covariate-Adjustment and Outcome Prediction using Electronic Health Record Data
Brian D Williamson, Richard Wyss, Elizabeth A Stuart +4
Real-world data, such as administrative claims and electronic health records, are increasingly used for safety monitoring and to help guide regulatory decision-making. In these set…