PrEGAN: Privacy-Enhanced Clinical EMR Generation: Leveraging GAN Model for Customer De-Identification

Privacy in medical records while data sharing is a major concern for distributed learning models. The dataset generated and shared via Electronic Medical Records (EMR) consist of sensitive medical information such as patient identify and experts' recommendations, and causes setbacks in training...

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Veröffentlicht in:	IEEE transactions on consumer electronics 2024-08, Vol.70 (3), p.6166-6173
Hauptverfasser:	Thouheed Ahmed, Syed, Sivakami, R., Vinoth Kumar, V., Mahesh, T. R., Bhatia Khan, Surbhi, Mashat, Arwa, Almusharraf, Ahlam
Format:	Artikel
Sprache:	eng
Schlagworte:	biomedical GAN Biomedical imaging Computational modeling Data models Data privacy de-identification electronic health records EMR Generative adversarial networks generative adversarial networks (GAN) Mathematical models PrEGAN Privacy Privacy enhanced GAN
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