[HTML][HTML] SynSigGAN: Generative adversarial networks for synthetic biomedical signal generation
Simple Summary This paper proposes a novel generative adversarial networks model,
SynSigGAN, to generate any kind of synthetic biomedical signals. The generation of …
SynSigGAN, to generate any kind of synthetic biomedical signals. The generation of …
[HTML][HTML] Generating synthetic fermentation data of Shindari, a traditional Jeju beverage, using multiple imputation ensemble and generative adversarial networks
Fermentation is an age-old technique used to preserve food by restoring proper microbial
balance. Boiled barley and nuruk are fermented for a short period to produce Shindari, a …
balance. Boiled barley and nuruk are fermented for a short period to produce Shindari, a …
Analyse du signal électrophysiologique dans le contexte de la localisation du noyau sous-thalamique pour la stimulation cérébrale profonde
T Martin - 2024 - theses.hal.science
La Stimulation Cérébrale Profonde est une thérapie symptomatique de la maladie de
Parkinson qui vise à améliorer la qualité de vie du patient. Pour être efficace, cette …
Parkinson qui vise à améliorer la qualité de vie du patient. Pour être efficace, cette …
Synthetic Electronic Medical Record Generation using Generative Adversarial Networks
MR Beyki - 2021 - vtechworks.lib.vt.edu
It has been a while that computers have replaced our record books, and medical records are
no exception. Electronic Health Records (EHR) are digital version of a patient's medical …
no exception. Electronic Health Records (EHR) are digital version of a patient's medical …