Generating Multi-label Discrete Electronic Health Records using Generative Adversarial Networks閱讀筆記
本文參考的原始論文地址https://arxiv.org/abs/1703.06490v1 摘要 獲取電子健康記錄(EHR)數據推動了醫學研究的計算進步。然而，各種對隱私的關注，會限制我們的訪問和協作。共享綜合EHR數據可以減少風險。該文提出了一種新的方法-醫學生成對抗網絡(MedGAN)，來生成真實的綜合EHRs。基於作爲輸入EHR數據集，medGAN可以通過自動編碼器和生成對抗性網
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相關文章
- 1. Generating Adversarial Examples with Adversarial Networks閱讀筆記
- 2. BEGAN: Boundary Equilibrium Generative Adversarial Networks閱讀筆記
- 3. 【閱讀筆記】Generative Adversarial Nets
- 4. Generative Adversarial Networks: An Overview文獻閱讀筆記
- 5. 論文：Scalable and accurate deep learning for electronic health records研讀筆記
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- 7. 論文閱讀筆記：GENERATING NATURAL ADVERSARIAL EXAMPLES
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- 9. [advGAN]Generating Adversarial Examples With Adversarial Networks
- 10. 論文閱讀——Deformable Medical Image Registration Using Generative Adversarial Networks