Propensity Weighted federated learning for treatment effect estimation in distributed imbalanced environments
Published in Computers in Biology and Medicine. Elsevier, 2024
Propensity Weighted federated learning for treatment effect estimation in distributed imbalanced environments (2024)
PW FedAvg: An adaptation of FedAvg on Treatment Effect Disentagled Variational Autoencoder (TEDVAE) to imbalanced environments, where the distribution of treated and control groups is very different accross hospitals.
Cite as:
@article{almodovar2024propensity,
title={Propensity Weighted federated learning for treatment effect estimation in distributed imbalanced environments},
author={Almod{\'o}var, Alejandro and Parras, Juan and Zazo, Santiago},
journal={Computers in Biology and Medicine},
volume={178},
pages={108779},
year={2024},
publisher={Elsevier}
}