mlsanityData to 14 Oct 2026

Synthetic Acute Hypotension and Sepsis Datasets Based on MIMIC-III and Published as Part of the Health Gym Project

arXiv 2112.03914 ↗First posted 7 Dec 2021cs.LG cs.AIcited by 5

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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.

Builds on

2 of 10 references.

References · 2

  1. 2017Improved Training of Wasserstein GANscited by 2,235
  2. 2020Interpretable Off-Policy Evaluation in Reinforcement Learning by Highlighting Influential Transitionscited by 41

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2022: 1; 2023: 1; 2024: 1; 2025: 0; 2026: 2.

5 papers.

Similar, not cited

Close in wording, no citation either way

  1. 2023Synthetic Health-related Longitudinal Data with Mixed-type Variables Generated using Diffusion Models
  2. 2019Sepsis World Model: A MIMIC-based OpenAI Gym "World Model" Simulator for Sepsis Treatment
  3. 2024CK4Gen: A Knowledge Distillation Framework for Generating High-Utility Synthetic Survival Datasets in Healthcare
  4. 2024Generative AI for Synthetic Data Across Multiple Medical Modalities: A Systematic Review of Recent Developments and Challenges
  5. 2025Synthetic Survival Data Generation for Heart Failure Prognosis Using Deep Generative Models
  6. 2026Generative Modeling for Physiological Signals ↗
  7. 2025Exploring a Graph-based Approach to Offline Reinforcement Learning for Sepsis Treatment
  8. 2024The Minimum Information about CLinical Artificial Intelligence Checklist for Generative Modeling Research (MI-CLAIM-GEN)