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Generative Adversarial Networks for Anonymized Healthcare of Lung Cancer Patients
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
inferredcites →https://doi.org/10.1007/978-3-030-45385-5openalex-snapshot
Bioinformatics and Biomedical Engineering
inferredcites →https://doi.org/10.1007/978-3-658-40442-0_9openalex-snapshot
Generative Adversarial Nets
inferredcites →https://doi.org/10.1016/j.media.2019.101552openalex-snapshot
Generative adversarial network in medical imaging: A review
inferredcites →https://doi.org/10.1109/jiot.2021.3051158openalex-snapshot
Digital Twin for Intelligent Context-Aware IoT Healthcare Systems
inferredcites →https://doi.org/10.1109/lsp.2020.3025020openalex-snapshot
Improving GANs for Speech Enhancement
inferredcites →https://doi.org/10.1186/s12874-020-00977-1openalex-snapshot
Generation and evaluation of synthetic patient data
inferredcites →https://doi.org/10.1186/s40537-019-0197-0openalex-snapshot
A survey on Image Data Augmentation for Deep Learning
inferredcites →https://doi.org/10.3233/faia190139openalex-snapshot
Towards a Healthcare Digital Twin1
inferredcites →https://doi.org/10.3389/fgene.2018.00031openalex-snapshot
Digital Twins in Health Care: Ethical Implications of an Emerging Engineering Paradigm
inferredcites →https://doi.org/10.3390/electronics10040389openalex-snapshot
Generating Synthetic ECGs Using GANs for Anonymizing Healthcare Data
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
inferred← citeshttps://doi.org/10.1002/cpt.3001openalex-snapshot
A Case for Synthetic Data in Regulatory Decision‐Making in Europe
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Healthcare 5.0: Enabling Technologies and Potential Use Cases
inferred← citeshttps://doi.org/10.1007/978-3-032-22582-5_6openalex-snapshot
Assessing the Performance of GAN for Healthcare Applications Utilizing Synthetic Datasets
inferred← citeshttps://doi.org/10.1007/978-981-19-9090-8_11openalex-snapshot
Performance Evaluation of ML Models in the Health Care Domain to Classify Liver Disease: A Case Study
inferred← citeshttps://doi.org/10.1007/s11869-025-01710-xopenalex-snapshot
An accurate two-stage deep machine learning aided air quality estimation based on multiple gases from aerial images
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Revolutionizing solar energy resources: The central role of generative AI in elevating system sustainability and efficiency
inferred← citeshttps://doi.org/10.1016/j.compbiomed.2023.107655openalex-snapshot
Deep Generative Models: The winning key for large and easily accessible ECG datasets?
inferred← citeshttps://doi.org/10.1016/j.eswa.2025.126950openalex-snapshot
Artificial generation of survey data on the expected bitterness of beer
inferred← citeshttps://doi.org/10.1016/j.heliyon.2023.e19390openalex-snapshot
Literature review of digital twin in healthcare
inferred← citeshttps://doi.org/10.1016/j.ijmedinf.2024.105413openalex-snapshot
Can I trust my fake data – A comprehensive quality assessment framework for synthetic tabular data in healthcare
inferred← citeshttps://doi.org/10.1101/2024.02.20.24303096openalex-snapshot
Patient digital twins: an introduction based on a scoping review
inferred← citeshttps://doi.org/10.1109/access.2025.3528736openalex-snapshot
Digital Twin’s Anatomy: A Cross-Sector Framework With Healthcare Validation
inferred← citeshttps://doi.org/10.1109/bhi56158.2022.9926856openalex-snapshot
Class Activation Maps for the disentanglement and occlusion of identity attributes in medical imagery
inferred← citeshttps://doi.org/10.1109/cbms55023.2022.00079openalex-snapshot
Patient identification methods based on medical imagery and their impact on patient privacy and open medical data
inferred← citeshttps://doi.org/10.1109/chase52844.2021.00044openalex-snapshot
Digital Twins in cancer: State-of-the-art and open research
inferred← citeshttps://doi.org/10.1109/tii.2025.3540473openalex-snapshot
Generative AI-Empowered Digital Twin: A Comprehensive Survey With Taxonomy
inferred← citeshttps://doi.org/10.1111/coin.12682openalex-snapshot
Deep learning for personalized health monitoring and prediction: A review
inferred← citeshttps://doi.org/10.1186/s12967-025-06371-zopenalex-snapshot
From virtual to reality: innovative practices of digital twins in tumor therapy
inferred← citeshttps://doi.org/10.21015/vtse.v12i3.1853openalex-snapshot
Generating synthetic data in biomedical imaging by designing GANs
inferred← citeshttps://doi.org/10.2196/58504openalex-snapshot
Definitions and Characteristics of Patient Digital Twins Being Developed for Clinical Use: Scoping Review
inferred← citeshttps://doi.org/10.25103/jestr.172.22openalex-snapshot
Digital Twin Concept and its Applications: A Review
inferred← citeshttps://doi.org/10.3390/app112210823openalex-snapshot
A Generative Adversarial Network Structure for Learning with Small Numerical Data Sets
inferred← citeshttps://doi.org/10.3390/app14177438openalex-snapshot
Generative Adversarial Networks in Business and Social Science
inferred← citeshttps://doi.org/10.3390/cancers15143608openalex-snapshot
Deep Learning for Medical Image-Based Cancer Diagnosis
inferred← citeshttps://doi.org/10.3390/diseases11040134openalex-snapshot
Optimizing Clinical Diabetes Diagnosis through Generative Adversarial Networks: Evaluation and Validation
inferred← citeshttps://doi.org/10.3390/electronics11010032openalex-snapshot
Contextual Information Aided Generative Adversarial Network for Low-Light Image Enhancement
inferred← citeshttps://doi.org/10.3390/electronics11203277openalex-snapshot
Statistical Validation of Synthetic Data for Lung Cancer Patients Generated by Using Generative Adversarial Networks
inferred← citeshttps://doi.org/10.3390/electronics12081921openalex-snapshot
Digital Twin Technology: New Frontiers for Personalized Healthcare
inferred← citeshttps://doi.org/10.3390/electronics15173795openalex-snapshot
Global Perspectives on AI-Based Digital Twins in Smart Rehabilitation and Physiotherapy: Convergence of IoMT, Multiphysics Modeling, and Wireless Bio-Integrated Sensing
inferred← citeshttps://doi.org/10.3390/fi16090343openalex-snapshot
Artificial Intelligence to Reshape the Healthcare Ecosystem
inferred← citeshttps://doi.org/10.3390/sym14020339openalex-snapshot
An Integrated Framework Based on GAN and RBI for Learning with Insufficient Datasets
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