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Generating Synthetic Electronic Health Record Data Using Generative Adversarial Networks: Tutorial
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
inferredcites →https://doi.org/10.1001/jama.2017.18391openalex-snapshot
Big Data and Machine Learning in Health Care
inferredcites →https://doi.org/10.1001/jama.2018.5602openalex-snapshot
Big Data and Predictive Analytics
inferredcites →https://doi.org/10.1001/jama.2019.11365openalex-snapshot
Big Data, Big Tech, and Protecting Patient Privacy
inferredcites →https://doi.org/10.1001/jamanetworkopen.2021.0184openalex-snapshot
Assessing Missing Data Assumptions in EHR-Based Studies: A Complex and Underappreciated Task
inferredcites →https://doi.org/10.1007/s41666-020-00077-1openalex-snapshot
Predicting Missing Values in Medical Data Via XGBoost Regression
inferredcites →https://doi.org/10.1007/s44163-021-00016-yopenalex-snapshot
Synthetic data use: exploring use cases to optimise data utility
inferredcites →https://doi.org/10.1016/j.compmedimag.2019.101684openalex-snapshot
MedGAN: Medical image translation using GANs
inferredcites →https://doi.org/10.1016/j.jbi.2021.103977openalex-snapshot
Membership inference attacks against synthetic health data
inferredcites →https://doi.org/10.1016/j.neucom.2019.12.136openalex-snapshot
Generation and evaluation of privacy preserving synthetic health data
inferredcites →https://doi.org/10.1016/j.neucom.2022.04.053openalex-snapshot
Synthetic data generation for tabular health records: A systematic review
inferredcites →https://doi.org/10.1016/j.patter.2021.100347openalex-snapshot
Addressing bias in big data and AI for health care: A call for open science
inferredcites →https://doi.org/10.1016/s0140-6736(22)00232-xopenalex-snapshot
Synthetic patient data in health care: a widening legal loophole
inferredcites →https://doi.org/10.1038/s41467-022-35295-1openalex-snapshot
A Multifaceted benchmarking of synthetic electronic health record generation models
inferredcites →https://doi.org/10.1038/s41551-021-00751-8openalex-snapshot
Synthetic data in machine learning for medicine and healthcare
inferredcites →https://doi.org/10.1038/s41591-018-0272-7openalex-snapshot
Privacy in the age of medical big data
inferredcites →https://doi.org/10.1038/s41591-018-0300-7openalex-snapshot
High-performance medicine: the convergence of human and artificial intelligence
inferredcites →https://doi.org/10.1038/s41597-022-01899-xopenalex-snapshot
MIMIC-IV, a freely accessible electronic health record dataset
inferredcites →https://doi.org/10.1038/s41597-023-01945-2openalex-snapshot
Author Correction: MIMIC-IV, a freely accessible electronic health record dataset
inferredcites →https://doi.org/10.1038/s41746-020-00353-9openalex-snapshot
Generating high-fidelity synthetic patient data for assessing machine learning healthcare software
inferredcites →https://doi.org/10.1038/s41746-023-00834-7openalex-snapshot
Generating synthetic mixed-type longitudinal electronic health records for artificial intelligent applications
inferredcites →https://doi.org/10.1093/bib/bbab489openalex-snapshot
Evaluating the state of the art in missing data imputation for clinical data
inferredcites →https://doi.org/10.1093/bioinformatics/btq126openalex-snapshot
PheWAS: demonstrating the feasibility of a phenome-wide scan to discover gene–disease associations
inferredcites →https://doi.org/10.1093/jamia/ocaa196openalex-snapshot
The National COVID Cohort Collaborative (N3C): Rationale, design, infrastructure, and deployment
inferredcites →https://doi.org/10.1093/jamia/ocaa262openalex-snapshot
SynTEG: a framework for temporal structured electronic health data simulation
inferredcites →https://doi.org/10.1093/jamia/ocac131openalex-snapshot
Keeping synthetic patients on track: feedback mechanisms to mitigate performance drift in longitudinal health data simulation
inferredcites →https://doi.org/10.1093/jamia/ocz161openalex-snapshot
Ensuring electronic medical record simulation through better training, modeling, and evaluation
inferredcites →https://doi.org/10.1109/access.2019.2905015openalex-snapshot
Recent Progress on Generative Adversarial Networks (GANs): A Survey
inferredcites →https://doi.org/10.1109/cbms.2019.00036openalex-snapshot
Generating and Evaluating Synthetic UK Primary Care Data: Preserving Data Utility & Patient Privacy
inferredcites →https://doi.org/10.1109/ichi.2019.8904776openalex-snapshot
Deep Imputation of Temporal Data
inferredcites →https://doi.org/10.1109/ijcnn54540.2023.10191367openalex-snapshot
Time-series Anonymization of Tabular Health Data using Generative Adversarial Network
inferredcites →https://doi.org/10.1145/3636424openalex-snapshot
A Survey of Generative Adversarial Networks for Synthesizing Structured Electronic Health Records
inferredcites →https://doi.org/10.1146/annurev-publhealth-040617-014208openalex-snapshot
Big Data in Public Health: Terminology, Machine Learning, and Privacy
inferredcites →https://doi.org/10.1371/journal.pdig.0000082openalex-snapshot
Synthetic data in health care: A narrative review
inferredcites →https://doi.org/10.1609/aaai.v34i01.5401openalex-snapshot
CONAN: Complementary Pattern Augmentation for Rare Disease Detection
inferredcites →https://doi.org/10.2196/14325openalex-snapshot
Mapping ICD-10 and ICD-10-CM Codes to Phecodes: Workflow Development and Initial Evaluation
inferredcites →https://doi.org/10.2196/23139openalex-snapshot
Evaluating Identity Disclosure Risk in Fully Synthetic Health Data: Model Development and Validation
inferredcites →https://doi.org/10.2196/medinform.8960openalex-snapshot
Characterizing and Managing Missing Structured Data in Electronic Health Records: Data Analysis
inferredcites →https://doi.org/10.3233/shti230136openalex-snapshot
Domain Knowledge-Driven Generation of Synthetic Healthcare Data
inferredcites →https://doi.org/10.3390/e23091165openalex-snapshot
The Problem of Fairness in Synthetic Healthcare Data
inferredcites →https://doi.org/10.48550/arxiv.1703.06490openalex-snapshot
Generating Multi-label Discrete Patient Records using Generative Adversarial Networks
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
inferred← citeshttps://doi.org/10.1002/advs.202516196openalex-snapshot
High‐Fidelity Synthetic Data Replicates Clinical Prediction Performance in a Million‐Patient Diabetes Cohort
inferred← citeshttps://doi.org/10.1007/978-3-032-11358-0_30openalex-snapshot
A Methodology for the Generation and Evaluation of Tabular Synthetic Data: A Case Study in Data Analysis in Intensive Care Units
inferred← citeshttps://doi.org/10.1007/s10462-026-11535-4openalex-snapshot
Privacy-preserving in foundation models: a systematic review of techniques, threats, and trade-offs
inferred← citeshttps://doi.org/10.1007/s10728-025-00537-yopenalex-snapshot
Navigating Healthcare AI Governance: the Comprehensive Algorithmic Oversight and Stewardship Framework for Risk and Equity
inferred← citeshttps://doi.org/10.1016/j.cca.2026.120878openalex-snapshot
Synthetic data in the clinical laboratory: methods, applications, and future prospects
inferred← citeshttps://doi.org/10.1016/j.ipej.2026.09.005openalex-snapshot
Dynamic simulation and digital twins in atrial fibrillation: Complementary roles and current limitations
inferred← citeshttps://doi.org/10.1016/j.jbi.2026.105012openalex-snapshot
Community medical centers struggle to produce well-calibrated clinical prediction models: Data augmentation can help
inferred← citeshttps://doi.org/10.1038/s41746-025-01786-wopenalex-snapshot
Framework for bias evaluation in large language models in healthcare settings
inferred← citeshttps://doi.org/10.1080/24725579.2025.2510966openalex-snapshot
Optimizing clustering of electronic health tabular data: generative adversarial networks and Dirichlet process mixture models for advance healthcare analytics
inferred← citeshttps://doi.org/10.1101/2025.06.16.25329699openalex-snapshot
Rural Medical Centers Struggle to Produce Well-Calibrated Clinical Prediction Models: Data Augmentation Can Help
inferred← citeshttps://doi.org/10.1109/acdsa65407.2025.11166453openalex-snapshot
A Proof-of-Concept Study Using Generative AI for Structured PGHD Extraction in Remote Patient Monitoring and Mobile Health
inferred← citeshttps://doi.org/10.1109/acdsa67686.2026.11467939openalex-snapshot
Leveraging Big Data Analytics for Childhood Obesity Research: The BIO-STREAMS European Digital Infrastructure
inferred← citeshttps://doi.org/10.1109/ichi64645.2025.00067openalex-snapshot
MLM4SynMed: Masked Language Modelling for Synthetic Free-text Medical Records Generation
inferred← citeshttps://doi.org/10.1109/infoteh68759.2026.11477705openalex-snapshot
GenAI as a Tool for Scientists and Researchers
inferred← citeshttps://doi.org/10.1109/isacc65211.2025.10969346openalex-snapshot
Generative Adversarial Networks for Synthetic Data Generation in Privacy-Preserving Health Informatics
inferred← citeshttps://doi.org/10.1109/isacc65211.2025.10969418openalex-snapshot
Radiographic Imaging and AI: A Systematic Review on Applications in Medical Imaging
inferred← citeshttps://doi.org/10.1109/ojcs.2026.3650842openalex-snapshot
Redefining Elderly Care With Agentic AI: Challenges and Opportunities
inferred← citeshttps://doi.org/10.1145/3721201.3725440openalex-snapshot
Approximate Knowledge Graphs: Privacy-Preserving Healthcare Data Synthesis via LLM-Driven approximation
inferred← citeshttps://doi.org/10.1186/s12911-026-03396-2openalex-snapshot
Deep generative hidden Markov models for synthetic patient data generation: a novel approach for medical AI research
inferred← citeshttps://doi.org/10.1186/s12982-026-01464-6openalex-snapshot
Scalable cloud–AI architecture for synthetic healthcare data generation and anomaly modeling: a simulation-based study
inferred← citeshttps://doi.org/10.2196/100772openalex-snapshot
A Patient Simulation Framework for Risk Assessment of Conversational Health Care AI: Development and Evaluation Study
inferred← citeshttps://doi.org/10.2197/ipsjjip.34.161openalex-snapshot
Generative Synthesis of Precipitation Radar Data for Disaster IT Testbed
inferred← citeshttps://doi.org/10.22399/ijcesen.5089openalex-snapshot
Federated Learning in the Cloud: A New Era for Data Privacy and Integration
inferred← citeshttps://doi.org/10.33093/jiwe.2026.5.2.1openalex-snapshot
Synthetic Data Generation for Healthcare Machine Learning: A Case Study in Vital Signs and Diagnostic Predictions
inferred← citeshttps://doi.org/10.3389/fdgth.2025.1620270openalex-snapshot
Synthetic data in medical imaging within the EHDS: a path forward for ethics, regulation, and standards
inferred← citeshttps://doi.org/10.3390/app16052235openalex-snapshot
Predicting ICU Readmission Afte Intracerebral Hemorrhage: A Deep Learning Framework Using MIMIC Time-Series Data
inferred← citeshttps://doi.org/10.3934/aci.2024009openalex-snapshot
Finnish perspective on using synthetic health data to protect privacy: the PRIVASA project
inferred← citeshttps://doi.org/10.4018/979-8-3373-5641-9.ch006openalex-snapshot
Generative AI Approaches for Synthetic Health Data Generation
inferred← citeshttps://doi.org/10.47670/wuwijar20261rmmatnopenalex-snapshot
Adaptive Generative AI Framework for Creating Rare-Disease Synthetic EHRs with Built-In Bias Mitigation and Privacy Guarantees
inferred← citeshttps://doi.org/10.53297/18293336-2025.1-48openalex-snapshot
GENERATION OF SYNTHETIC MOVEMENTS BY GENERATIVE ADVERSARIAL NETWORKS FOR IMPROVING THE RECOGNITION OF RARE ACTIONS
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