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Comparison of Synthetic Data Generation Techniques for Control Group Survival Data in Oncology Clinical Trials: Simulation Study

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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1002/cpt.2480openalex-snapshot
Use of Real‐World Evidence to Drive Drug Development Strategy and Inform Clinical Trial Design
inferredcites →https://doi.org/10.1007/s00264-023-05830-wopenalex-snapshot
Artificial intelligence publications: synthetic data, patients, and papers
inferredcites →https://doi.org/10.1016/j.cct.2018.01.003openalex-snapshot
Clinical trials recruitment planning: A proposed framework from the Clinical Trials Transformation Initiative
inferredcites →https://doi.org/10.1016/j.conctc.2018.08.001openalex-snapshot
Factors associated with clinical trials that fail and opportunities for improving the likelihood of success: A review
inferredcites →https://doi.org/10.1016/j.imu.2022.101118openalex-snapshot
GANerAid: Realistic synthetic patient data for clinical trials
inferredcites →https://doi.org/10.1023/a:1010933404324openalex-snapshot
Random Forests
inferredcites →https://doi.org/10.1037/pag0000046openalex-snapshot
Using Classification and Regression Trees (CART) and random forests to analyze attrition: Results from two simulations.
inferredcites →https://doi.org/10.1038/s41586-021-03430-5openalex-snapshot
Evaluating eligibility criteria of oncology trials using real-world data and AI
inferredcites →https://doi.org/10.1038/s41598-023-38457-3openalex-snapshot
A comparison of synthetic data generation and federated analysis for enabling international evaluations of cardiovascular health
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/s41746-023-00771-5openalex-snapshot
Patient-centric synthetic data generation, no reason to risk re-identification in biomedical data analysis
inferredcites →https://doi.org/10.1038/s41746-023-00927-3openalex-snapshot
Harnessing the power of synthetic data in healthcare: innovation, application, and privacy
inferredcites →https://doi.org/10.1093/jamia/ocaa303openalex-snapshot
Application of Bayesian networks to generate synthetic health data
inferredcites →https://doi.org/10.1093/jamiaopen/ooac067openalex-snapshot
Case report: evaluation of an open-source synthetic data platform for simulation studies
inferredcites →https://doi.org/10.1136/bmjopen-2012-002360openalex-snapshot
Methods to improve recruitment to randomised controlled trials: Cochrane systematic review and meta-analysis
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/10.1158/1055-9965.epi-17-0172openalex-snapshot
Protecting Privacy in Large Datasets—First We Assess the Risk; Then We Fuzzy the Data
inferredcites →https://doi.org/10.1186/s12874-020-00977-1openalex-snapshot
Generation and evaluation of synthetic patient data
inferredcites →https://doi.org/10.1186/s12874-022-01654-1openalex-snapshot
Generating high-fidelity synthetic time-to-event datasets to improve data transparency and accessibility
inferredcites →https://doi.org/10.1200/cci.23.00021openalex-snapshot
Synthetic Data Generation by Artificial Intelligence to Accelerate Research and Precision Medicine in Hematology
inferredcites →https://doi.org/10.1200/cci.23.00071openalex-snapshot
Status of Synthetic Data Generation for Structured Health Data
inferredcites →https://doi.org/10.1371/journal.pdig.0000082openalex-snapshot
Synthetic data in health care: A narrative review
inferredcites →https://doi.org/10.1371/journal.pone.0028071openalex-snapshot
A Systematic Review of Re-Identification Attacks on Health Data
inferredcites →https://doi.org/10.1634/theoncologist.2019-0175openalex-snapshot
Median Survival or Mean Survival: Which Measure Is the Most Appropriate for Patients, Physicians, and Policymakers?
inferredcites →https://doi.org/10.2196/18910openalex-snapshot
Reliability of Supervised Machine Learning Using Synthetic Data in Health Care: Model to Preserve Privacy for Data Sharing
inferredcites →https://doi.org/10.2196/29337openalex-snapshot
Understanding the Security and Privacy Concerns About the Use of Identifiable Health Data in the Context of the COVID-19 Pandemic: Survey Study of Public Attitudes Toward COVID-19 and Data-Sharing
inferredcites →https://doi.org/10.2196/publichealth.7344openalex-snapshot
Combining Participatory Influenza Surveillance with Modeling and Forecasting: Three Alternative Approaches
inferredcites →https://doi.org/10.3389/fonc.2021.695936openalex-snapshot
Application of Real-World Data to External Control Groups in Oncology Clinical Trial Drug Development
inferredcites →https://doi.org/10.37489/2782-3784-myrwd-45openalex-snapshot
Considerations for the design and conduct of externally controlled trials for drug and biological products

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

inferred← citeshttps://doi.org/10.1002/sim.70376openalex-snapshot
Maximal Local Privacy Loss—A New Method for Privacy Evaluation of Synthetic Datasets
inferred← citeshttps://doi.org/10.1007/s10260-025-00800-5openalex-snapshot
A flexible parametric approach to synthetic patients generation using health data
inferred← citeshttps://doi.org/10.1007/s10803-025-07176-1openalex-snapshot
Enhancing Developmental Language Disorder Identification with Artificial Intelligence: Development of an Explainable Screening App Using Real and Synthetic Data
inferred← citeshttps://doi.org/10.1016/b978-0-323-90509-1.00041-2openalex-snapshot
Major study types with designs, measures, and examples
inferred← citeshttps://doi.org/10.1016/j.resuscitation.2025.110904openalex-snapshot
Population-level impact of universal early AED implementation on out-of-hospital cardiac arrest outcomes: a machine learning analysis using synthetic patient data of 45-year projection study from Japan
inferred← citeshttps://doi.org/10.1038/s41568-026-00912-4openalex-snapshot
Artificial intelligence-generated synthetic data for cancer research and clinical trials
inferred← citeshttps://doi.org/10.1039/d5dd00504copenalex-snapshot
AI-driven natural product-based antiviral drug development: a technical overview
inferred← citeshttps://doi.org/10.1093/dmfr/twae044openalex-snapshot
An attempt to generate panoramic radiographs including jaw cysts using StyleGAN3
inferred← citeshttps://doi.org/10.1101/2025.06.09.25329247openalex-snapshot
Assessing synthetic data generation utility for cohort data secondary use
inferred← citeshttps://doi.org/10.1109/iccsp68173.2026.11539533openalex-snapshot
Interpretable Logistic Modeling of Multi-Agent Cytotoxicity in Gingival Cells: A Mechanistic-Computational Framework for Periodontal Survival Prediction
inferred← citeshttps://doi.org/10.2174/0127724328311400240823062829openalex-snapshot
Leveraging Generative AI for Drug Safety and Pharmacovigilance
inferred← citeshttps://doi.org/10.2196/66821openalex-snapshot
Augmenting Insufficiently Accruing Oncology Clinical Trials Using Generative Models: Validation Study
inferred← citeshttps://doi.org/10.2196/71297openalex-snapshot
Privacy-by-Design Approach to Generate Two Virtual Clinical Trials for Multiple Sclerosis and Release Them as Open Datasets: Evaluation Study
inferred← citeshttps://doi.org/10.2196/74116openalex-snapshot
Synthetic Tabular Data Generation Under Horizontal Federated Learning Environments in Acute Myeloid Leukemia: Case-Based Simulation Study
inferred← citeshttps://doi.org/10.3389/fdmed.2026.1710316openalex-snapshot
Denoising autoencoder framework for reconstructing missing periodontal clinical records
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
inferred← citeshttps://doi.org/10.4018/979-8-3373-5641-9.ch003openalex-snapshot
Synthetic Healthcare Data in Generation, Validation, and Integration for Ethical and Scalable Health Innovation
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