Article

Federated Target Trial Emulation using Distributed Observational Data for Treatment Effect Estimation

2025-05-05

Abstract excerpt

Target trial emulation (TTE) aims to estimate treatment effects by simulating randomized controlled trials using real-world observational data. Applying TTE across distributed datasets shows great promise in improving generalizability and power but is always infeasible due to privacy and data-sharing constraints. Here we propose a Federated Learning-based TTE framework, FL-TTE, that enables TTE across multiple sit...

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work: 9fb0a78e-cefb-5fc8-b38f-881153bcbb65
DOI: 10.1101/2025.05.02.25326905

Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest

Federated Target Trial Emulation using Distributed Observational Data for Treatment Effect EstimationDOI 10.1101/2025.05.02.25326905Read

FedWeight: Mitigating Covariate Shift of Federated Learning on Electronic Health Records Data through Patients Re-weightingSemantic proximity Read

FedWeight: Mitigating Covariate Shift of Federated Learning on Electronic Health Records Data through Patients Re-weightingSemantic proximity Read

Privacy-first health research with federated learningSemantic proximity Read

Ten Quick Tips for Biomedical Federated LearningSemantic proximity Read

Development of a federated learning approach to predict acute kidney injury in adult hospitalized patients with COVID-19 in New York CitySemantic proximity Read

Federated Learning for ICU Mortality Prediction: Balancing Accuracy and Privacy in a Multi-Hospital SettingSemantic proximity Read

The R.O.A.D. to clinical trial emulationSemantic proximity Read

Federated Learning used for predicting outcomes in SARS-COV-2 patientsSemantic proximity Read

Toward Real-World Deployment of Federated Learning in Healthcare: A Comprehensive Review of Hybrid Models and Data Simulation ToolsSemantic proximity Read

Efficacy of federated learning on genomic data: a study on the UK Biobank and the 1000 Genomes ProjectSemantic proximity Read

Data Heterogeneity in Federated Learning with Electronic Health Records: Case Studies of Risk Prediction for Acute Kidney Injury and Sepsis Diseases in Critical CareSemantic proximity Read

Hierarchical Personalized Continual Federated Learning for Real Time Risk Prediction of Chronic DiseasesSemantic proximity Read