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EVA: Generating Longitudinal Electronic Health Records Using Conditional Variational Autoencoders.

, , , , , , and . MLHC, volume 149 of Proceedings of Machine Learning Research, page 260-282. PMLR, (2021)

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TASTE: temporal and static tensor factorization for phenotyping electronic health records., , , , , , , and . CHIL, page 193-203. ACM, (2020)Using recurrent neural network models for early detection of heart failure onset., , , and . J. Am. Medical Informatics Assoc., 24 (2): 361-370 (2017)Longitudinal Adversarial Attack on Electronic Health Records Data., , , and . WWW, page 2558-2564. ACM, (2019)Generating Multi-label Discrete Patient Records using Generative Adversarial Networks., , , , , and . MLHC, volume 68 of Proceedings of Machine Learning Research, page 286-305. PMLR, (2017)EVA: Generating Longitudinal Electronic Health Records Using Conditional Variational Autoencoders., , , , , , and . MLHC, volume 149 of Proceedings of Machine Learning Research, page 260-282. PMLR, (2021)Electronic Health Record Audit Logs: An Alternative Approach to Workflow Analysis., , , and . AMIA, AMIA, (2015)LEAP: Learning to Prescribe Effective and Safe Treatment Combinations for Multimorbidity., , , , and . KDD, page 1315-1324. ACM, (2017)MiME: Multilevel Medical Embedding of Electronic Health Records for Predictive Healthcare., , , and . NeurIPS, page 4552-4562. (2018)SUSTain: Scalable Unsupervised Scoring for Tensors and its Application to Phenotyping., , , , , , , and . KDD, page 2080-2089. ACM, (2018)EVA: Generating Longitudinal Electronic Health Records Using Conditional Variational Autoencoders., , , , , and . CoRR, (2020)