Synthetic Acute Hypotension and Sepsis Datasets Based on MIMIC-III and Published as Part of the Health Gym Project
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Abstract (arXiv)
These two synthetic datasets comprise vital signs, laboratory test results, administered fluid boluses and vasopressors for 3,910 patients with acute hypotension and for 2,164 patients with sepsis in the Intensive Care Unit (ICU). The patient cohorts were built using previously published inclusion and exclusion criteria and the data were created using Generative Adversarial Networks (GANs) and the MIMIC-III Clinical Database. The risk of identity disclosure associated with the release of these data was estimated to be very low (0.045%). The datasets were generated and published as part of the Health Gym, a project aiming to publicly distribute synthetic longitudinal health data for developing machine learning algorithms (with a particular focus on offline reinforcement learning) and for educational purposes.
Key facts. Cited by 5 papers in the map (data through 14 Oct 2026). Builds on 2 of its 10 references that are in the map. First posted on arXiv 7 Dec 2021.
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2 of 10 references.
References · 2
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Citing papers per year: 2022: 1; 2023: 1; 2024: 1; 2025: 0; 2026: 2.
5 papers.
- 2023Deep Imputation of Missing Values in Time Series Health Data: A Review with Benchmarkingcited by 30
- 2022The Health Gym: Synthetic Health-Related Datasets for the Development of Reinforcement Learning Algorithmscited by 19
- 2024Contrastive Representation for Data Filtering in Cross-Domain Offline Reinforcement Learningcited by 18
- 2026Mining Electronic Health Records to Investigate Effectiveness of Ensemble Deep Clusteringcited by 2
- 2026A Unified Benchmark for Dynamic Medical Treatment Reinforcement Learningcited by 0
- 2026A Unified Benchmark for Dynamic Medical Treatment Reinforcement Learning31 May 2026
- 2026Mining Electronic Health Records to Investigate Effectiveness of Ensemble Deep Clustering8 Apr 2026
- 2024Contrastive Representation for Data Filtering in Cross-Domain Offline Reinforcement Learning10 May 2024
- 2023Deep Imputation of Missing Values in Time Series Health Data: A Review with Benchmarking10 Feb 2023
- 2022The Health Gym: Synthetic Health-Related Datasets for the Development of Reinforcement Learning Algorithms12 Mar 2022
Similar, not cited
Close in wording, no citation either way
- 2023Synthetic Health-related Longitudinal Data with Mixed-type Variables Generated using Diffusion Models
- 2019Sepsis World Model: A MIMIC-based OpenAI Gym "World Model" Simulator for Sepsis Treatment
- 2024CK4Gen: A Knowledge Distillation Framework for Generating High-Utility Synthetic Survival Datasets in Healthcare
- 2024Generative AI for Synthetic Data Across Multiple Medical Modalities: A Systematic Review of Recent Developments and Challenges
- 2025Synthetic Survival Data Generation for Heart Failure Prognosis Using Deep Generative Models
- 2026Generative Modeling for Physiological Signals ↗
- 2025Exploring a Graph-based Approach to Offline Reinforcement Learning for Sepsis Treatment
- 2024The Minimum Information about CLinical Artificial Intelligence Checklist for Generative Modeling Research (MI-CLAIM-GEN)