Synthetic data generation for tabular health records: A systematic review

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Addressing 6 challenges in generative AI for digital health: A scoping review

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A scoping review of privacy and utility metrics in medical synthetic data

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A Multifaceted benchmarking of synthetic electronic health record generation models

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A Survey of Generative Adversarial Networks for Synthesizing Structured Electronic Health Records

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Synthetic data in biomedicine via generative artificial intelligence

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Synthetic Tabular Data Evaluation in the Health Domain Covering Resemblance, Utility, and Privacy Dimensions

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Challenges and opportunities of generative models on tabular data

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GAN-Based Approaches for Generating Structured Data in the Medical Domain

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Mimicking clinical trials with synthetic acute myeloid leukemia patients using generative artificial intelligence

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Can I trust my fake data – A comprehensive quality assessment framework for synthetic tabular data in healthcare

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Synthetic data generation in healthcare: A scoping review of reviews on domains, motivations, and future applications

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Preserving privacy in healthcare: A systematic review of deep learning approaches for synthetic data generation

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Synthetic Patient Data Generation and Evaluation in Disease Prediction Using Small and Imbalanced Datasets

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Syntheval: a framework for detailed utility and privacy evaluation of tabular synthetic data

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Explanatory predictive model for COVID-19 severity risk employing machine learning, shapley addition, and LIME

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Optimizing starch content prediction in kudzu: Integrating hyperspectral imaging and deep learning with WGAN-GP

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Comprehensive evaluation framework for synthetic tabular data in health: fidelity, utility and privacy analysis of generative models with and without privacy guarantees

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A review on generative AI models for synthetic medical text, time series, and longitudinal data

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Large language models and synthetic health data: progress and prospects

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Privacy Mechanisms and Evaluation Metrics for Synthetic Data Generation: A Systematic Review

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Deep Convolutional Generative Adversarial Networks to Enhance Artificial Intelligence in Healthcare: A Skin Cancer Application

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Non-imaging Medical Data Synthesis for Trustworthy AI: A Comprehensive Survey

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Challenges and perspectives in use of artificial intelligence to support treatment recommendations in clinical oncology

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Enhanced Conditional GAN for High-Quality Synthetic Tabular Data Generation in Mobile-Based Cardiovascular Healthcare

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Synthetic Data Generation for Healthcare: Exploring Generative Adversarial Networks Variants for Medical Tabular Data

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Overcoming data scarcity in radiomics/radiogenomics using synthetic radiomic features

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Generating Synthetic Electronic Health Record Data Using Generative Adversarial Networks: Tutorial

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TTVAE: Transformer-based generative modeling for tabular data generation

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Synthetic data: revisiting the privacy-utility trade-off

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On the Quality of Synthetic Generated Tabular Data

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On the fidelity versus privacy and utility trade-off of synthetic patient data

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Multi-Agent Systems and Foundation Models Enable Autonomous Supply Chains: Opportunities and Challenges

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An interpretable machine learning-based model for shear resistance prediction of CFRP-strengthened RC beams using experimental and synthetic dataset

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Systematic Review of Generative Modelling Tools and Utility Metrics for Fully Synthetic Tabular Data

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Improving irregular temporal modeling by integrating synthetic data to the electronic medical record using conditional GANs: a case study of fluid overload prediction in the intensive care unit

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An evaluation of the replicability of analyses using synthetic health data

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Private pathological assessment via machine learning and homomorphic encryption

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Influence of Optimization Algorithms and Computational Complexity on Concrete Compressive Strength Prediction Machine Learning Models for Concrete Mix Design

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Encryption and Generation of Images for Privacy-Preserving Machine Learning in Smart Manufacturing

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Exploring Innovative Approaches to Synthetic Tabular Data Generation

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Evaluating the Utility and Privacy of Synthetic Breast Cancer Clinical Trial Data Sets

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Synthetic Data and Its Utility in Pathology and Laboratory Medicine

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How good is your synthetic data? SynthRO, a dashboard to evaluate and benchmark synthetic tabular data

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An Evaluation Framework for Synthetic Data Generation Models

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Synthetic data as external control arms in scarce single-arm clinical trials

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A systematic review of privacy-preserving techniques for synthetic tabular health data

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Enhancing public research on citizen data: An empirical investigation of data synthesis using Statistics New Zealand’s Integrated Data Infrastructure

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Generation of a Realistic Synthetic Laryngeal Cancer Cohort for AI Applications

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Challenges and applications in generative AI for clinical tabular data in physiology

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Preserving information while respecting privacy through an information theoretic framework for synthetic health data generation

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Evaluation of synthetic electronic health records: A systematic review and experimental assessment

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On the Adoption of Modern Technologies to Fight the COVID-19 Pandemic: A Technical Synthesis of Latest Developments

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Tabular transformer generative adversarial network for heterogeneous distribution in healthcare

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Contribution of Synthetic Data Generation towards an Improved Patient Stratification in Palliative Care

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An enhancement of machine learning model performance in disease prediction with synthetic data generation

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Generating synthetic multidimensional molecular time series data for machine learning: considerations

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Examining the role of artificial intelligence to advance knowledge and address barriers to research in eating disorders

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Self-Supervision Improves Diffusion Models for Tabular Data Imputation

Liu, Y., Ajanthan, T., Husain, H., & Nguyen, V. (2024) · ACM International Conference on Information and Knowledge Management (CIKM) · doi:10.1145/3627673.3679829 · Cited by 13

Generating synthetic electronic health record data: a methodological scoping review with benchmarking on phenotype data and open-source software

Chen, X., Wu, Z., Shi, X., Cho, H., & Mukherjee, B. (2025) · Journal of the American Medical Informatics Association · doi:10.1093/jamia/ocaf082 · Cited by 28

Methods for Generating and Evaluating Synthetic Longitudinal Patient Data: A Systematic Review

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Moving Conditional GAN Close to Data: Synthetic Tabular Data Generation and Its Experimental Evaluation

Majeed, A., & Hwang, S. O. (2024) · IEEE Transactions on Big Data · doi:10.1109/tbdata.2024.3442534 · Cited by 12

Status of Synthetic Data Generation for Structured Health Data

Emam, K. E. (2023) · JCO Clinical Cancer Informatics · doi:10.1200/cci.23.00071 · Cited by 12

Revolutionizing Healthcare with Generative Artificial Intelligence Technologies

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Data-centric AI to Improve Early Detection of Mental Illness

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A Gaussian-based WGAN-GP oversampling approach for solving the class imbalance problem

Zhou, Q., & Sun, B. (2024) · International Journal of Applied Mathematics and Computer Science · doi:10.61822/amcs-2024-0021 · Cited by 10

On the evaluation of synthetic longitudinal electronic health records

Achterberg, J., Haas, M., & Spruit, M. R. (2024) · BMC Medical Research Methodology · doi:10.1186/s12874-024-02304-4 · Cited by 14

Feature group tabular transformer: a novel approach to traffic crash modeling and causality analysis

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Conditional Generative Models for Synthetic Tabular Data: Applications for Precision Medicine and Diverse Representations

Liu, K., & Altman, R. B. (2025) · Annual Review of Biomedical Data Science · doi:10.1146/annurev-biodatasci-103123-094844 · Cited by 14

Use of Synthetic Data in Maritime Applications for the Problem of Steam Turbine Exergy Analysis

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A Text-to-tabular Approach to Generate Synthetic Patient Data using LLMs

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MedWGAN based synthetic dataset generation for Uveitis pathology

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Synthetic Subject Generation with Coupled Coherent Time Series Data

Larrea, X., Hernandez, M., Epelde, G., Beristain, A., Molina, C., Alberdi, A., Rankin, D., Bamidis, P. D., & Konstantinidis, E. I. (2022) · International Conference on Time Series and Forecasting (ITISE) · doi:10.3390/engproc2022018007 · Cited by 9

Fed-OLF: Federated Oversampling Learning Framework for Imbalanced Software Defect Prediction Under Privacy Protection

Hu, X., Zheng, M., Zhu, R., Zhang, X., & Jin, Z. G. (2025) · IEEE Transactions on Reliability · doi:10.1109/tr.2024.3524064 · Cited by 8

Explainable evaluation of generative adversarial networks for wearables data augmentation

Narteni, S., Orani, V., Ferrari, E., Verda, D., Cambiaso, E., & Mongelli, M. (2025) · Engineering Applications of Artificial Intelligence · doi:10.1016/j.engappai.2025.110133 · Cited by 12

Fidelity-agnostic synthetic data generation improves utility while retaining privacy

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Survey on Tabular Data Privacy and Synthetic Data Generation in Industry 4.0

Koubeissy, H., Amine, A., Kamradt, M., & Makhoul, A. (2025) · Applied Intelligence · doi:10.1007/s10489-025-06823-5 · Cited by 10

A comprehensive evaluation framework for synthetic medical tabular data generation

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An explainable dataset linking facial phenotypes and genes to rare genetic diseases

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A Paradigm Shift From an Experimental-Based to a Simulation-Based Framework Using Motion-Capture Driven MIMO Radar Data Synthesis

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Using UMAP for Partially Synthetic Healthcare Tabular Data Generation and Validation

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Privacy Vulnerabilities in Marginals-based Synthetic Data

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Realistic synthetic dataset generation for cyber-physical systems: a performance evaluation

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Membership Inference Attacks and Differential Privacy: A Study Within the Context of Generative Models

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Time-series Anonymization of Tabular Health Data using Generative Adversarial Network

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