GAN
Showing 1 - 7 of 7 results-
Generating Multi-label Discrete Patient Records using Generative Adversarial Networks
- Published on: January, 2018
- Siddharth Biswal, Edward Choi, Walter F. Stewart, Bradley Malin, Jimeng Sun, Jon Duke
- Code Available
Researchers have a controlled access to the Electronic Health Records (EHR) data as it is composed of personal identifiers and sensitive medical info ...
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Fetal ECG Extraction from Maternal ECG using Attention based Cycle GAN
- Published on: January, 2021
- A., Mohebian, K.A., Wahid, K., M.R., S., Marateb, H.R. and Tavakolian, shahim Vedaei, Dinh
- Code Available
Non-invasive fetal electrocardiogram (FECG) is used to monitor the electrical pulse of the fetal heart. Decomposing the FECG signal from maternal ECG ...
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CorGAN-Correlation Capturing Convolutional Neural Networks for Generating Synthetic Healthcare Records
- Published on: February, 2020
- Edward A. Fox, Amirsina Torfi
- Code Available
In healthcare domain, researchers face a lot of privacy challenges when it comes to create a deep learning model using electronic health record (EHR) ...
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GAIN-Missing Data Imputation using Generative Adversarial Nets
- Published on: January, 2018
- Mihaela van der Schaar, James Jordon, Jinsung Yoon
- Code Available
GAIN comprises of a method for imputing missing data by adapting the Generative Adversarial Nets (GAN) framework. GAN models consists of generator and ...
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Differentially Private Synthetic Medical Data Generation using Convolutional GANs
- Published on: December, 2020
- Chandan K. Reddy, Edward A. Fox, Amirsina Torfi
- Code Available
Torfi et. al. have built a privacy-preserving GAN model using Renyi differential privacy for generating synthetic medical data from real health record ...
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DP-CGAN-Differentially Private Synthetic Data and Label Generation
- Published on: February, 2018
- Kaixiang Lin, Liyang Xie, Fei Wang, Jiayu Zhou, Shu Wang
- Code Available
Generative Adversarial Network (GAN) provide a promising direction in the studies where data availability is limited. However, GANs can easily remeber ...
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Breaking Medical Data Sharing Boundaries by Employing Artificial Radiographs
- Published on: November, 2019
- Volkmar Schulz, Tianyu Han, Daniel Truhn, Dorit Merhof, Fabian Kiessling, Christoph Haarburger, Sven Nebelung,...
- Code Available
GANs can be used to generate deceivingly real looking radiographs and to merge databases of radiological images without disclosing patient sensitive i ...