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Differentially Private Medical Texts Generation Using Generative Neural Networks
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
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Machine learning, natural language programming, and electronic health records: The next step in the artificial intelligence journey?
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Automated systems for the de-identification of longitudinal clinical narratives: Overview of 2014 i2b2/UTHealth shared task Track 1
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Automatic detection of protected health information from clinic narratives
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Hidden Markov model using Dirichlet process for de-identification
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Practical applications for natural language processing in clinical research: The 2014 i2b2/UTHealth shared tasks
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Clinical information extraction applications: A literature review
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De-identification of electronic health record using neural network
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Google searches do not correlate with melanoma incidence in majority English speaking countries
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Natural language generation for electronic health records
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Generation and evaluation of artificial mental health records for Natural Language Processing
inferredcites →https://doi.org/10.1038/s41746-020-0307-6openalex-snapshot
Wearable radio-frequency sensing of respiratory rate, respiratory volume, and heart rate
inferredcites →https://doi.org/10.1038/sdata.2016.35openalex-snapshot
MIMIC-III, a freely accessible critical care database
inferredcites →https://doi.org/10.1056/nejmlim035027openalex-snapshot
HIPAA Regulations — A New Era of Medical-Record Privacy?
inferredcites →https://doi.org/10.1080/08839514.2020.1718343openalex-snapshot
A review of Automatic end-to-end De-Identification: Is High Accuracy the Only Metric?
inferredcites →https://doi.org/10.1093/bib/bbx139openalex-snapshot
Privacy-preserving techniques of genomic data—a survey
inferredcites →https://doi.org/10.1093/jamia/ocw156openalex-snapshot
De-identification of patient notes with recurrent neural networks
inferredcites →https://doi.org/10.1093/jamia/ocy068openalex-snapshot
Opportunities and challenges in developing deep learning models using electronic health records data: a systematic review
inferredcites →https://doi.org/10.1093/jamia/ocz200openalex-snapshot
Deep learning in clinical natural language processing: a methodical review
inferredcites →https://doi.org/10.1093/llc/fqu064openalex-snapshot
Significance testing of word frequencies in corpora
inferredcites →https://doi.org/10.1097/00005650-199907000-00009openalex-snapshot
Health Insurance Portability and Accountability Act of 1996
inferredcites →https://doi.org/10.1109/bhi19528.2012openalex-snapshot
Proceedings of 2012 IEEE-EMBS International Conference on Biomedical and Health Informatics
inferredcites →https://doi.org/10.1109/bibm.2018.8621223openalex-snapshot
Generation of Synthetic Electronic Medical Record Text
inferredcites →https://doi.org/10.1109/bibmw.2007.4425389openalex-snapshot
Proceedings 2007 IEEE international conference on bioinformatics and biomedicine
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inferredcites →https://doi.org/10.1109/eurosp.2018.00035openalex-snapshot
SoK: Security and Privacy in Machine Learning
inferredcites →https://doi.org/10.1109/globalsip.2013.6736861openalex-snapshot
Stochastic gradient descent with differentially private updates
inferredcites →https://doi.org/10.1109/icnn.1996.548916openalex-snapshot
Learning task-dependent distributed representations by backpropagation through structure
inferredcites →https://doi.org/10.1109/jbhi.2017.2767063openalex-snapshot
Deep EHR: A Survey of Recent Advances in Deep Learning Techniques for Electronic Health Record (EHR) Analysis
inferredcites →https://doi.org/10.1109/sp.2017.41openalex-snapshot
Membership Inference Attacks Against Machine Learning Models
inferredcites →https://doi.org/10.1111/j.1475-6773.2005.00444.xopenalex-snapshot
Measuring Diagnoses: ICD Code Accuracy
inferredcites →https://doi.org/10.1145/2810103.2813687openalex-snapshot
Privacy-Preserving Deep Learning
inferredcites →https://doi.org/10.1145/2976749.2978318openalex-snapshot
Deep Learning with Differential Privacy
inferredcites →https://doi.org/10.1145/319950.320022openalex-snapshot
A general language model for information retrieval
inferredcites →https://doi.org/10.1186/1472-6947-8-32openalex-snapshot
Automated de-identification of free-text medical records
inferredcites →https://doi.org/10.1377/hlthaff.23.2.116openalex-snapshot
Physicians’ Use Of Electronic Medical Records: Barriers And Solutions
inferredcites →https://doi.org/10.1561/0400000042openalex-snapshot
The Algorithmic Foundations of Differential Privacy
inferredcites →https://doi.org/10.18653/v1/2020.emnlp-main.500openalex-snapshot
BERT-ATTACK: Adversarial Attack Against BERT Using BERT
inferredcites →https://doi.org/10.18653/v1/2020.privatenlp-1.5openalex-snapshot
Differentially Private Language Models Benefit from Public Pre-training
inferredcites →https://doi.org/10.18653/v1/k16-1002openalex-snapshot
Generating Sentences from a Continuous Space
inferredcites →https://doi.org/10.18653/v1/w19-1905openalex-snapshot
Towards Automatic Generation of Shareable Synthetic Clinical Notes Using Neural Language Models
inferredcites →https://doi.org/10.2466/pms.103.2.412-414openalex-snapshot
Measures of Effect Size for Chi-Squared and Likelihood-Ratio Goodness-of-Fit Tests
inferredcites →https://doi.org/10.3115/v1/d14-1162openalex-snapshot
Glove: Global Vectors for Word Representation
inferredcites →https://doi.org/10.4135/9781412952644.n199openalex-snapshot
Health Insurance Portability and Accountability Act
inferredcites →https://doi.org/10.4230/lipics.cosit.2022.18openalex-snapshot
AI-Assisted Pipeline for Dynamic Generation of Trustworthy Health Supplement Content at Scale
inferredcites →https://doi.org/10.48550/arxiv.1301.3781openalex-snapshot
Efficient Estimation of Word Representations in Vector Space
inferredcites →https://doi.org/10.48550/arxiv.1606.05908openalex-snapshot
Tutorial on Variational Autoencoders
inferredcites →https://doi.org/10.48550/arxiv.1609.04747openalex-snapshot
An overview of gradient descent optimization algorithms
inferredcites →https://doi.org/10.48550/arxiv.1706.02633openalex-snapshot
Real-valued (Medical) Time Series Generation with Recurrent Conditional GANs
inferredcites →https://doi.org/10.48550/arxiv.1710.06963openalex-snapshot
Learning Differentially Private Recurrent Language Models
inferredcites →https://doi.org/10.48550/arxiv.1712.00164openalex-snapshot
Generative Adversarial Networks for Electronic Health Records: A Framework for Exploring and Evaluating Methods for Predicting Drug-Induced Laboratory Test Trajectories
inferredcites →https://doi.org/10.48550/arxiv.1801.07736openalex-snapshot
MaskGAN: Better Text Generation via Filling in the______
inferredcites →https://doi.org/10.48550/arxiv.1802.08232openalex-snapshot
The Secret Sharer: Evaluating and Testing Unintended Memorization in Neural Networks
inferredcites →https://doi.org/10.48550/arxiv.1810.01570openalex-snapshot
A Deep Learning Architecture for De-identification of Patient Notes: Implementation and Evaluation
inferredcites →https://doi.org/10.5555/944919.944966openalex-snapshot
A neural probabilistic language model
inferredcites →https://doi.org/10.5555/972450.972454openalex-snapshot
Accurate methods for the statistics of surprise and coincidence
inferredcites →https://doi.org/10.6028/nist.ir.8053openalex-snapshot
De-identification of personal information
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
inferred← citeshttps://doi.org/10.1007/978-3-032-00633-2_11openalex-snapshot
Mitigating Bias in Recruitment: A Practical Approach to CV De-identification Considering Privacy Sensitive Information
inferred← citeshttps://doi.org/10.1007/978-981-95-3462-3_8openalex-snapshot
Differentially Private Fine-Tuning of Large Language Models: A Survey
inferred← citeshttps://doi.org/10.1016/j.compbiomed.2025.109834openalex-snapshot
Generative AI for synthetic data across multiple medical modalities: A systematic review of recent developments and challenges
inferred← citeshttps://doi.org/10.1016/j.heliyon.2023.e20962openalex-snapshot
“Chatting with ChatGPT”: Analyzing the factors influencing users' intention to Use the Open AI's ChatGPT using the UTAUT model
inferred← citeshttps://doi.org/10.1038/s41598-024-81170-yopenalex-snapshot
De-identification is not enough: a comparison between de-identified and synthetic clinical notes
inferred← citeshttps://doi.org/10.1038/s41598-025-86890-3openalex-snapshot
Evaluating GPT models for clinical note de-identification
inferred← citeshttps://doi.org/10.1038/s41746-024-01409-wopenalex-snapshot
A review on generative AI models for synthetic medical text, time series, and longitudinal data
inferred← citeshttps://doi.org/10.1038/s41746-025-02280-zopenalex-snapshot
Differential privacy for medical deep learning: methods, tradeoffs, and deployment implications
inferred← citeshttps://doi.org/10.1093/jamia/ocaf037openalex-snapshot
Robust privacy amidst innovation with large language models through a critical assessment of the risks
inferred← citeshttps://doi.org/10.1108/978-1-83708-724-220251001openalex-snapshot
Factors Affecting the Acceptance of ChatGPT: A Study of Malaysian University Students
inferred← citeshttps://doi.org/10.1109/access.2026.3715238openalex-snapshot
A Comprehensive Survey of Generative AI: Applications and Future Directions Across Domains
inferred← citeshttps://doi.org/10.1109/dsc63484.2024.00039openalex-snapshot
A Method for Generating Medical Text Data by Integrating Spatiotemporal Attributes and Implicit State Transitions
inferred← citeshttps://doi.org/10.1145/3563950openalex-snapshot
Synthetic Behavior Sequence Generation Using Generative Adversarial Networks
inferred← citeshttps://doi.org/10.1145/3583593openalex-snapshot
TS-GAN: Time-series GAN for Sensor-based Health Data Augmentation
inferred← citeshttps://doi.org/10.1145/3743093.3771004openalex-snapshot
BALANCE: A Fairness-Aware Framework for Privacy-Preserving Synthetic Clinical Text Generation
inferred← citeshttps://doi.org/10.28945/5503openalex-snapshot
Systematic Literature Review of the Development of Data Science Applications in Healthcare
inferred← citeshttps://doi.org/10.3390/app122312320openalex-snapshot
Privacy and Utility of Private Synthetic Data for Medical Data Analyses
inferred← citeshttps://doi.org/10.7759/cureus.73874openalex-snapshot
Assessing the Quality, Readability, and Acceptability of AI-Generated Information in Plastic and Aesthetic Surgery
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