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Synthetic Tabular Data Based on Generative Adversarial Networks in Health Care: Generation and Validation Using the Divide-and-Conquer Strategy
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
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Hyperparameter Optimization
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General framework for class-specific feature selection
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Use of national clinical databases for informing and for evaluating health care policies
inferredcites →https://doi.org/10.1016/j.imu.2022.101118openalex-snapshot
GANerAid: Realistic synthetic patient data for clinical trials
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An introduction to ROC analysis
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Shifting machine learning for healthcare from development to deployment and from models to data
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Privacy-preserving healthcare informatics: a review
inferredcites →https://doi.org/10.1093/jamia/ocy142openalex-snapshot
Synthesizing electronic health records using improved generative adversarial networks
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/icsgrc.2011.5991826openalex-snapshot
Overview of use of decision tree algorithms in machine learning
inferredcites →https://doi.org/10.1126/scitranslmed.aab3719openalex-snapshot
A targeted real-time early warning score (TREWScore) for septic shock
inferredcites →https://doi.org/10.1136/bmjopen-2020-043497openalex-snapshot
Can synthetic data be a proxy for real clinical trial data? A validation study
inferredcites →https://doi.org/10.1155/2014/781670openalex-snapshot
Impact of HbA1c Measurement on Hospital Readmission Rates: Analysis of 70,000 Clinical Database Patient Records
inferredcites →https://doi.org/10.1155/2020/8865808openalex-snapshot
A Semantic-Based Approach for Managing Healthcare Big Data: A Survey
inferredcites →https://doi.org/10.1161/circoutcomes.118.005122openalex-snapshot
Privacy-Preserving Generative Deep Neural Networks Support Clinical Data Sharing
inferredcites →https://doi.org/10.1214/18-aos1777openalex-snapshot
Quantile regression under memory constraint
inferredcites →https://doi.org/10.1371/journal.pdig.0000082openalex-snapshot
Synthetic data in health care: A narrative review
inferredcites →https://doi.org/10.3389/fpubh.2020.00164openalex-snapshot
Generative Adversarial Networks and Its Applications in Biomedical Informatics
inferredcites →https://doi.org/10.3390/electronics10040389openalex-snapshot
Generating Synthetic ECGs Using GANs for Anonymizing Healthcare Data
inferredcites →https://doi.org/10.4143/crt.2018.704openalex-snapshot
Report of the Korean Association of Lung Cancer Registry (KALC-R), 2014
inferredcites →https://doi.org/10.4143/crt.2022.264openalex-snapshot
Five-Year Overall Survival and Prognostic Factors in Patients with Lung Cancer: Results from the Korean Association of Lung Cancer Registry (KALC-R) 2015
inferredcites →https://doi.org/10.48550/arxiv.1811.11264openalex-snapshot
Synthesizing Tabular Data using Generative Adversarial Networks
inferredcites →https://doi.org/10.48550/arxiv.2102.10771openalex-snapshot
Divide-and-conquer methods for big data analysis
inferredcites →https://doi.org/10.7861/fhj.2022-0013openalex-snapshot
Generative adversarial networks and synthetic patient data: current challenges and future perspectives
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
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Generating Synthetic Medical Dataset Using Generative AI: A Case Study
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Synthetic Data in Healthcare and Drug Development: Definitions, Regulatory Frameworks, Issues
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Generative Artificial Intelligence as a Tool for Improving the Accuracy of Classification Models
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Machine Learning-Driven Acute Oral Toxicity Predictions by Random Forest
inferred← citeshttps://doi.org/10.1007/978-3-032-31170-2_44openalex-snapshot
Synthetic Data Generation with CTGAN for Enhanced Stroke Risk Prediction
inferred← citeshttps://doi.org/10.1007/978-3-032-34377-2_10openalex-snapshot
SynGenEva: A Generator-Agnostic Evaluation Protocol for Synthetic Tabular Data
inferred← citeshttps://doi.org/10.1007/978-981-92-2006-9_41openalex-snapshot
Bridging Data Scarcity and Physical Consistency in Liquefaction Assessment Using Physics-Informed Generative Models
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Prediction of Cerebrospinal Fluid (CSF) Pressure with Generative Adversarial Network Synthetic Plasma-CSF Biomarker Pairing
inferred← citeshttps://doi.org/10.1007/s41060-025-00816-wopenalex-snapshot
Synthetic Data Generation for Healthcare: Exploring Generative Adversarial Networks Variants for Medical Tabular Data
inferred← citeshttps://doi.org/10.1016/j.procs.2026.05.111openalex-snapshot
Synthetic Data-Augmented Modeling for Early Detection and Progression of CKD
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Artificial intelligence-generated synthetic data for cancer research and clinical trials
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Tabular transformer generative adversarial network for heterogeneous distribution in healthcare
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Synthetic tabular health data generation: a practical comparison between correlation and model-based statistical approach and the conditional generative adversarial network approach
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Tabular Data Augmentation Using Artificial Intelligence: A Systematic Review and Taxonomic Framework
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Evaluating Synthesized Data From Generative AI Through Conventional Data Analytics
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FairTabFormer: Mitigating Bias in Synthetic Network Traffic Data
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AI-Enhanced OER Observatory: A Framework for Personalized Inclusive Learning
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An Improved Lung Cancer Prediction Algorithm using Generative Adversarial Network in Modern Healthcare
inferred← citeshttps://doi.org/10.1109/icici68867.2026.11565005openalex-snapshot
A GAN-Augmented Ensemble Learning Framework for Early Heart Disease Risk Prediction
inferred← citeshttps://doi.org/10.1109/icmlt69916.2026.11688336openalex-snapshot
AI-Generated Medical Datasets for Research and Innovation
inferred← citeshttps://doi.org/10.1109/rcsm67767.2025.11506724openalex-snapshot
Benchmarking Statistical and Deep Generative Models for Assessing Synthetic Data Quality and Predictive Performance
inferred← citeshttps://doi.org/10.1186/s12911-024-02731-9openalex-snapshot
How good is your synthetic data? SynthRO, a dashboard to evaluate and benchmark synthetic tabular data
inferred← citeshttps://doi.org/10.1186/s12911-026-03648-1openalex-snapshot
An integrated evaluation framework for synthetic clinical data in severely imbalanced settings: fidelity, privacy-risk profiling, and diagnostic utility
inferred← citeshttps://doi.org/10.2196/52508openalex-snapshot
Consolidated Reporting Guidelines for Prognostic and Diagnostic Machine Learning Models (CREMLS)
inferred← citeshttps://doi.org/10.2196/preprints.52508openalex-snapshot
Consolidated Reporting Guidelines for Prognostic and Diagnostic Machine Learning Models (CREMLS) (Preprint)
inferred← citeshttps://doi.org/10.25259/jksus_69_2025openalex-snapshot
Adversarial validation of causal identifiability assumptions in model-based inference of diseases from multi-level omics and clinical data
inferred← citeshttps://doi.org/10.3389/fmed.2026.1894314openalex-snapshot
GAN-enhanced digital twins for biomarker-guided cancer immunotherapy and adoptive cell therapy: a mini review
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A Big Data Pipeline Approach for Predicting Real-Time Pandemic Hospitalization Risk
inferred← citeshttps://doi.org/10.3390/electronics13101965openalex-snapshot
Exploring Innovative Approaches to Synthetic Tabular Data Generation
inferred← citeshttps://doi.org/10.3390/jvd5040029openalex-snapshot
Realistic Synthetic Electronic Health Record Data Generation for Cardiovascular Risk Prediction
inferred← citeshttps://doi.org/10.5753/sbcas.2026.21649openalex-snapshot
Hy-Synergy: geração sintética de dados tabulares em saúde guiada por diagnóstico local
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