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Incorporation of Synthetic Data Generation Techniques within a Controlled Data Processing Workflow in the Health and Wellbeing Domain
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
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Privacy-Preserving Anomaly Detection Using Synthetic Data
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SMOOTH-GAN: Towards Sharp and Smooth Synthetic EHR Data Generation
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Applications of Generative Adversarial Networks (GANs): An Updated Review
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An Application of Machine Learning for Plasma Current Quench Studies via Synthetic Data Generation
inferredcites →https://doi.org/10.1016/j.ins.2020.06.019openalex-snapshot
A novel approach to create synthetic biomedical signals using BiRNN
inferredcites →https://doi.org/10.1016/j.neucom.2019.12.136openalex-snapshot
Generation and evaluation of privacy preserving synthetic health data
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The future of digital health with federated learning
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Synthesizing electronic health records using improved generative adversarial networks
inferredcites →https://doi.org/10.1109/access.2022.3144765openalex-snapshot
A Multi-Dimensional Evaluation of Synthetic Data Generators
inferredcites →https://doi.org/10.1109/bigdata47090.2019.9005476openalex-snapshot
Utility and Privacy Assessments of Synthetic Data for Regression Tasks
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/embc.2018.8512470openalex-snapshot
Synthetic Sensor Data Generation for Health Applications: A Supervised Deep Learning Approach
inferredcites →https://doi.org/10.1109/icdm.2017.93openalex-snapshot
Boosting Deep Learning Risk Prediction with Generative Adversarial Networks for Electronic Health Records
inferredcites →https://doi.org/10.1109/ijcnn.2018.8489106openalex-snapshot
SensoryGANs: An Effective Generative Adversarial Framework for Sensor-based Human Activity Recognition
inferredcites →https://doi.org/10.1109/ijcnn52387.2021.9534001openalex-snapshot
TSA-GAN: A Robust Generative Adversarial Networks for Time Series Augmentation
inferredcites →https://doi.org/10.1109/isbi.2018.8363678openalex-snapshot
GAN-based synthetic brain MR image generation
inferredcites →https://doi.org/10.1109/jbhi.2020.2980262openalex-snapshot
Anonymization Through Data Synthesis Using Generative Adversarial Networks (ADS-GAN)
inferredcites →https://doi.org/10.1109/smartgridcomm.2018.8587464openalex-snapshot
Generative Adversarial Network for Synthetic Time Series Data Generation in Smart Grids
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On the Utility of Synthetic Data
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A Baseline for Attribute Disclosure Risk in Synthetic Data
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Privacy-Preserving Generative Deep Neural Networks Support Clinical Data Sharing
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Generation and evaluation of synthetic patient data
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Reliability of Supervised Machine Learning Using Synthetic Data in Health Care: Model to Preserve Privacy for Data Sharing
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Federated Networks for Distributed Analysis of Health Data
inferredcites →https://doi.org/10.3390/biology9120441openalex-snapshot
SynSigGAN: Generative Adversarial Networks for Synthetic Biomedical Signal Generation
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Generating Synthetic ECGs Using GANs for Anonymizing Healthcare Data
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A Two-Stage GAN for High-Resolution Retinal Image Generation and Segmentation
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Evaluation of Data Augmentation Techniques for Facial Expression Recognition Systems
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SynSys: A Synthetic Data Generation System for Healthcare Applications
inferredcites →https://doi.org/10.36227/techrxiv.16610896.v1openalex-snapshot
Standardised Metrics and Methods for Synthetic Tabular Data Evaluation
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
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A Case for Synthetic Data in Regulatory Decision‐Making in Europe
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Standardized and extensible reference data model for clinical research in Living Labs
inferred← citeshttps://doi.org/10.1038/s41597-022-01784-7openalex-snapshot
The Health Gym: synthetic health-related datasets for the development of reinforcement learning algorithms
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Synthetic Tabular Data Evaluation in the Health Domain Covering Resemblance, Utility, and Privacy Dimensions
inferred← citeshttps://doi.org/10.1109/access.2024.3417608openalex-snapshot
Privacy Mechanisms and Evaluation Metrics for Synthetic Data Generation: A Systematic Review
inferred← citeshttps://doi.org/10.1109/cbms58004.2023.00341openalex-snapshot
Effect of incorporating metadata to the generation of synthetic time series in a healthcare context
inferred← citeshttps://doi.org/10.1109/jbhi.2022.3196697openalex-snapshot
Synthetic Patient Data Generation and Evaluation in Disease Prediction Using Small and Imbalanced Datasets
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Intelligent Detection of the Nanomaterials Spatial Structure with Synthetic Electron Microscopy Images
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Moving Conditional GAN Close to Data: Synthetic Tabular Data Generation and Its Experimental Evaluation
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Improved data query analysis techniques based on structure optimization and efficiency optimization
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Water Quality Monitoring for Smart Farming Using Machine Learning Approach
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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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A Semi-Supervised Machine Learning Approach in Predicting High-Risk Pregnancies in the Philippines
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Nonparametric Generation of Synthetic Data Using Copulas
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The Explanation and Sensitivity of AI Algorithms Supplied with Synthetic Medical Data
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Synthetic Subject Generation with Coupled Coherent Time Series Data
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Leveraging the Academic Artificial Intelligence Silecosystem to Advance the Community Oncology Enterprise
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Attribute-Centric and Synthetic Data Based Privacy Preserving Methods: A Systematic Review
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Dynamics Modeling of Industrial Robotic Manipulators: A Machine Learning Approach Based on Synthetic Data
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A Machine Learning-Based Risk Prediction Model During Pregnancy in Low-Resource Settings
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Finnish perspective on using synthetic health data to protect privacy: the PRIVASA project
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A variational autoencoder and neural network approach to generating synthetic data in well-being research
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Synthetic Healthcare Data in Generation, Validation, and Integration for Ethical and Scalable Health Innovation
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Development of a Deep Learning Model for the Prognosis of the Occurrence of Death from Stomach Cancer in Senegal
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An Architecture for Crowd Density Estimation in Heterogenous Opportunistic Environment
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