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Electronic Health Records (EHRs) are rich sources of patient-level data, offering valuable resources for medical data analysis.
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“MIMIC-III, a freely accessible critical care database”
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Jimmy Ba, Jamie Kiros and Geoffrey Hinton · 2016
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“Xgboost: A scalable tree boosting system”
Tianqi Chen and Carlos Guestrin · 2016
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Martin Wattenberg, Fernanda Viégas and Ian Johnson · 2016
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“Opportunities and challenges in developing risk prediction models with electronic health records data: a systematic review”
Benjamin Goldstein, Ann Navar, Michael. Pencina and John.. Ioannidis · 2017
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E. Choi et al · 2017
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“Real-valued (Medical) Time Series Generation with Recurrent Conditional GANs”, 2017
Cristóbal Esteban, Stephanie. Hyland and Gunnar Rätsch · 2017
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Ashish Vaswani et al · 2017
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“Deep EHR: A Survey of Recent Advances in Deep Learning Techniques for Electronic Health Record (EHR) Analysis”
Benjamin Shickel, Patrick Tighe, Azra Bihorac and Parisa Rashidi · 2018
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“Re-identification risk in HIPAA de-identified datasets: The MVA attack”
Victor Janmey and Peter Elkin · 2018
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“Generative Adversarial Network in Medical Imaging: A Review”
Xin Yi, Ekta Walia and Paul. Babyn · 2018
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“Improving Clinical Predictions through Unsupervised Time Series Representation Learning”, 2018
Xinrui Lyu et al · 2018
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“UMAP: Uniform Manifold Approximation and Projection for Dimension Reduction”
Leland McInnes and John Healy · 2018
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“Improved denoising diffusion probabilistic models”
Alexander Nichol and Prafulla Dhariwal · 2021
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“A Multifaceted benchmarking of synthetic electronic health record generation models”
Chao Yan et al · 2022
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“High-resolution image synthesis with latent diffusion models”
Robin Rombach et al · 2022
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“GT-GAN: General Purpose Time Series Synthesis with Generative Adversarial Networks”
Jinsung Jeon et al · 2022
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“Vector Quantized Diffusion Model for Text-to-Image Synthesis”
Shuyang Gu et al · 2022
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“Photorealistic Text-to-Image Diffusion Models with Deep Language Understanding”
Chitwan Saharia · 2022
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“Early hospital mortality prediction using vital signals”
Reza Sadeghi, Tanvi Banerjee and William Romine · 2018
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“Synthesizing electronic health records using improved generative adversarial networks”
Mrinal Baowaly, Chia-Ching Lin, Chao-Lin Liu and Kuan-Ta Chen · 2019
Cited alongside, same era.
“Time-series Generative Adversarial Networks”
Jinsung Yoon, Daniel Jarrett and Mihaela van Schaar · 2019
Cited alongside, same era.
“GRU-ODE-Bayes: Continuous modeling of sporadically-observed time series”
Edward De, Jaak Simm, Adam Arany and Yves Moreau · 2019
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“Generative modeling by estimating gradients of the data distribution”
Yang Song and Stefano Ermon · 2019
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“Socinf: Membership inference attacks on social media health data with machine learning”
Gaoyang Liu et al · 2019
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“Statistical analysis with missing data”
Roderick Little and Donald Rubin · 2019
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“TabDDPM: Modelling Tabular Data with Diffusion Models”
Akim Kotelnikov, Dmitry Baranchuk, Ivan Rubachev and Artem Babenko · 2022
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Sitan Chen et al · 2022
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“Applied missing data analysis”
Craig Enders · 2022
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“EHR-Safe: generating high-fidelity and privacy-preserving synthetic electronic health records”
Jinsung Yoon · 2023
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“Synthetic data in health care: a narrative review”
Aldren Gonzales, Guruprabha Guruswamy and Scott Smith · 2023
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Jie Gui et al · 2023
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“MedDiff: Generating Electronic Health Records using Accelerated Denoising Diffusion Model”
Huan He, Shifan Zhao, Yuanzhe Xi and Joyce Ho · 2023
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Ayan Das et al · 2023
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Ahmed Naseer et al · 2023
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Jin Li, Benjamin Cairns, Jingsong Li and Tingting Zhu · 2023
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“MIMIC-IV, a freely accessible electronic health record dataset” Article no. 1
Alistair.. Johnson et al · 2023
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“Missing data matter: an empirical evaluation of the impacts of missing EHR data in comparative effectiveness research”
Yizhao Zhou et al · 2023
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“A Flexible Generative Model for Heterogeneous Tabular EHR with Missing Modality”
Huan He et al · 2024
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