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Objective The aim of this study was to generate synthetic electronic health records (EHRs). The generated EHR data will be more realistic than those generated using the existing medical Generative Adversarial Network (medGAN) method. Materials and Methods We modified medGAN to obtain two synthetic data generation models—designated as medical Wasserstein GAN with gradient penalty (medWGAN) and medical boundary-seeking GAN (medBGAN)—and compared the results obtained using the three models. We used 2 databases: MIMIC-III and National Health Insurance Research Database (NHIRD), Taiwan. First, we trained the models and generated synthetic EHRs by using these three 3 models. We then analyzed and compared the models’ performance by using a few statistical methods (Kolmogorov–Smirnov test, dimension-wise probability for binary data, and dimension-wise average count for count data) and 2 machine learning tasks (association rule mining and prediction). Results We conducted a comprehensive analysis and found our models were adequately efficient for generating synthetic EHR data. The proposed models outperformed medGAN in all cases, and among the 3 models, boundary-seeking GAN (medBGAN) performed the best. Discussion To generate realistic synthetic EHR data, the proposed models will be effective in the medical industry and related research from the viewpoint of providing better services. Moreover, they will eliminate barriers including limited access to EHR data and thus accelerate research on medical informatics. Conclusion The proposed models can adequately learn the data distribution of real EHRs and efficiently generate realistic synthetic EHRs. The results show the superiority of our models over the existing model.

In this study, we report on a simple two-step casting process designed to create a stable superhydrophobic surface. This method possesses the advantages of being both simple and inexpensive as well as utilizing non-fluorine-containing compounds. Most interestingly, we found that the as-prepared surface possesses superhydrophobic properties not only for pure water but also for corrosive water under both acidic and basic conditions. Furthermore, the superhydrophobic polybenzoxazine surfaces had excellent environmental stability with regard to both heating and organic solvent treatment in terms of the contact angle to water.