Federated Markov Imputation: Privacy-Preserving Temporal Imputation in Multi-Centric ICU Environments

• URL: http://arxiv.org/abs/2509.20867v1
• Date: Thu, 25 Sep 2025 08:00:05 GMT
• Title: Federated Markov Imputation: Privacy-Preserving Temporal Imputation in Multi-Centric ICU Environments
• Authors: Christoph Düsing, Philipp Cimiano,
• Abstract summary: We propose Federated Markov Imputation (FMI), a privacy-preserving method that enables Intensive Care Units (ICUs) to collaboratively build global transition models for temporal imputation.<n>We evaluate FMI on a real-world sepsis onset prediction task using the MIMIC-IV dataset and show that it outperforms local imputation baselines.
• Score: 4.254099382808598
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Missing data is a persistent challenge in federated learning on electronic health records, particularly when institutions collect time-series data at varying temporal granularities. To address this, we propose Federated Markov Imputation (FMI), a privacy-preserving method that enables Intensive Care Units (ICUs) to collaboratively build global transition models for temporal imputation. We evaluate FMI on a real-world sepsis onset prediction task using the MIMIC-IV dataset and show that it outperforms local imputation baselines, especially in scenarios with irregular sampling intervals across ICUs.

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