Exploiting generative self-supervised learning for the assessment of biological images with lack of annotations

HIGHLIGHTS

• who: Alessio Mascolini from the Polytechnic University of, Italy have published the Article: Exploiting generative self-supervised learning for the assessment of biological images with lack of annotations, in the Journal: (JOURNAL)
• what: The authors show that Wasserstein Adversarial Networks enable highthroughput compound screening based on raw images. The authors demonstrate this by classifying active and inactive compounds tested for the inhibition of SARS-CoV-2 infection in two different cell models: the primary human renal cortical epithelial cells (HRCE) and the African green monkey kidney epithelial cells (VERO). Although the pretext task guides the . . .
  

   

  

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