A generative adversarial network model alternative to animal studies for clinical pathology assessment

Animal studies are unavoidable in evaluating chemical and drug safety. Generative Adversarial Networks (GANs) can generate synthetic animal data by learning from the legacy animal study results, thus may serve as an alternative approach to assess untested chemicals. AnimalGAN, a GAN method to simula...

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Detalles Bibliográficos
Autores principales: Chen, Xi, Roberts, Ruth, Liu, Zhichao, Tong, Weida
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2023
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10628291/
https://www.ncbi.nlm.nih.gov/pubmed/37932302
http://dx.doi.org/10.1038/s41467-023-42933-9

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10628291/
https://www.ncbi.nlm.nih.gov/pubmed/37932302
http://dx.doi.org/10.1038/s41467-023-42933-9

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