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Contributed

Health Data

Fri, Jan 15, 8:30 AM - 10:15 AM

6 Abstracts

Fed-GEE: Federated Generalized Estimating Equations for Privacy-Preserving Population-Level Inference for Multicenter Longitudinal Data

Co-authors: Soumik Purkayastha (University of Pittsburgh)

Clustered data Federated learning Population-average inference Privacy-preserving analysis Veteran Health

Causal Inference with Linked Data Files

Gauri Kamat (Brown University)

Co-authors: Roee Gutman (Brown University)

causal inference data integration missing data record linkage

Leveraging Known Entities to Improve Probabilistic Record Linkage for Health Data Integration

Co-authors: Roee Gutman (Brown University)

record linkage Bayesian analysis power prior data integration administrative health data Entity resolution Latent linkage structure

Fed-MAPSI: Federated Augmented Prediction-Powered Survival Inference with Partially Adjudicated Multi-Site EHR Data

Co-authors: Lili Zhao (Northwestern University)

electronic health records eal-world evidence computational phenotyping survival analysis prediction-powered inference federated learning digital health policy.

Data Reduction Methods to Detect Multimorbidity Patterns in Simulated Electronic Health Data

Nasiba Ahmed (University of Manitoba)

Co-authors: Songul Bozat-Emre (University of Manitoba), Lisa Lix (University of Manitoba), Paul Ronksley (University of Calgary)

multimorbidity data reduction methods matrix factorization sparse regularization

postlink: An R Package for Analyzing Imperfectly Linked Health Data

Priyanjali Bukke (University of Virginia)

Co-authors: Jiahao Cui, Roee Gutman (Brown University), Gauri Kamat (Brown University), Martin Slawski (University of Virginia)

data integration record linkage secondary analysis generalized linear models survival models missing data.

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