mlsanityData to 7 Oct 2026

The Health Gym: Synthetic Health-Related Datasets for the Development of Reinforcement Learning Algorithms

arXiv 2203.06369 ↗First posted 12 Mar 2022cs.LGcited by 19

Not on the map. Why?

Abstract (arXiv)

In recent years, the machine learning research community has benefited tremendously from the availability of openly accessible benchmark datasets. Clinical data are usually not openly available due to their highly confidential nature. This has hampered the development of reproducible and generalisable machine learning applications in health care. Here we introduce the Health Gym - a growing collection of highly realistic synthetic medical datasets that can be freely accessed to prototype, evaluate, and compare machine learning algorithms, with a specific focus on reinforcement learning. The three synthetic datasets described in this paper present patient cohorts with acute hypotension and sepsis in the intensive care unit, and people with human immunodeficiency virus (HIV) receiving antiretroviral therapy in ambulatory care. The datasets were created using a novel generative adversarial network (GAN). The distributions of variables, and correlations between variables and trends over time in the synthetic datasets mirror those in the real datasets. Furthermore, the risk of sensitive information disclosure associated with the public distribution of the synthetic datasets is estimated to be very low.

Key facts. Cited by 19 papers in the map (data through 7 Oct 2026). Builds on 24 of its 105 references that are in the map. First posted on arXiv 12 Mar 2022.

Builds on

24 of 105 references.

References · 24

  1. 2019PyTorch: An Imperative Style, High-Performance Deep Learning Librarycited by 20,160
  2. 2021Diffusion Models Beat GANs on Image Synthesiscited by 8,185
  3. 2022Generative Adversarial Networkscited by 5,603
  4. 2013Playing Atari with Deep Reinforcement Learningcited by 3,211
  5. 2017Improved Training of Wasserstein GANscited by 2,223
  6. 2014Conditional Generative Adversarial Netscited by 2,152
  7. 2020Offline Reinforcement Learning: Tutorial, Review, and Perspectives on Open Problemscited by 1,873
  8. 2016OpenAI Gymcited by 1,684
  9. 2020D4RL: Datasets for Deep Data-Driven Reinforcement Learningcited by 1,406
  10. 2018Off-Policy Deep Reinforcement Learning without Explorationcited by 1,227
  11. 2016Generative Adversarial Text to Image Synthesiscited by 735
  12. 2017Real-valued (Medical) Time Series Generation with Recurrent Conditional GANscited by 329
12 more
  1. 2017Generating Multi-label Discrete Patient Records using Generative Adversarial Networkscited by 197
  2. 2016DeepMind Labcited by 74
  3. 2017Deep Reinforcement Learning for Sepsis Treatmentcited by 71
  4. 2017Adversarial Feature Matching for Text Generationcited by 58
  5. 2021Generating Synthetic Mixed-type Longitudinal Electronic Health Records for Artificial Intelligent Applicationscited by 47
  6. 2020Interpretable Off-Policy Evaluation in Reinforcement Learning by Highlighting Influential Transitionscited by 41
  7. 2018Airline Passenger Name Record Generation using Generative Adversarial Networkscited by 19
  8. 2017Frustratingly Short Attention Spans in Neural Language Modelingcited by 18
  9. 2017Language Generation with Recurrent Generative Adversarial Networks without Pre-trainingcited by 14
  10. 2019Regional Tree Regularization for Interpretability in Black Box Modelscited by 14
  11. 2021Offline reinforcement learning with uncertainty for treatment strategies in sepsiscited by 9
  12. 2021Synthetic Acute Hypotension and Sepsis Datasets Based on MIMIC-III and Published as Part of the Health Gym Projectcited by 5

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2022: 2; 2023: 5; 2024: 3; 2025: 4; 2026: 5.

19 papers.

Sort:

By area:

  1. 2023Deep Imputation of Missing Values in Time Series Health Data: A Review with Benchmarkingcited by 29
  2. 2024Can I trust my fake data -- A comprehensive quality assessment framework for synthetic tabular data in healthcarecited by 17
  3. 2022Generating Synthetic Clinical Data that Capture Class Imbalanced Distributions with Generative Adversarial Networks: Example using Antiretroviral Therapy for HIVcited by 12
  4. 2024D5RL: Diverse Datasets for Data-Driven Deep Reinforcement Learningcited by 11
  5. 2023Synthetic Health-related Longitudinal Data with Mixed-type Variables Generated using Diffusion Modelscited by 9
  6. 2025Transfer Learning of Tabular Data by Finetuning Large Language Modelscited by 4
  7. 2025Generating Clinically Realistic EHR Data via a Hierarchy- and Semantics-Guided Transformercited by 4
  8. 2022Mitigating Health Data Poverty: Generative Approaches versus Resampling for Time-series Clinical Datacited by 2
  9. 2024Masked Clinical Modelling: A Framework for Synthetic and Augmented Survival Data Generationcited by 2
  10. 2023Methods for generating and evaluating synthetic longitudinal patient data: a systematic reviewcited by 1
  11. 2025Attention-Based Synthetic Data Generation for Calibration-Enhanced Survival Analysis: A Case Study for Chronic Kidney Disease Using Electronic Health Recordscited by 1
  12. 2026PRIME-CVD: A Parametrically Rendered Informatics Medical Environment for Education in Cardiovascular Risk Modellingcited by 1
7 more
  1. 2023Joint Distributional Learning via Cramer-Wold Distancecited by 0
  2. 2023Balanced Marginal and Joint Distributional Learning via Mixture Cramer-Wold Distancecited by 0
  3. 2025Critical Challenges and Guidelines in Evaluating Synthetic Tabular Data: A Systematic Reviewcited by 0
  4. 2026Evaluation metrics for temporal preservation in synthetic longitudinal patient datacited by 0
  5. 2026Counterfactually Safe Reinforcement Learningcited by 0
  6. 2026Synthetic but Not Realistic: The Evaluation Challenge in Generative Modelling for Structured Electronic Medical Recordscited by 0
  7. 2026Insulin4RL: Real-Time Insulin Management in the Intensive Care Unit for Offline Reinforcement Learningcited by 0