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Our interpretable machine learning in melanoma was published!

Updated: Aug 30

Highlights:

  • Generative deep network encoded latent representation of live-imaged melanoma cells

  • Supervised machine-learning classified metastatic efficiency using latent cell representations

  • Validated classifier prediction on melanoma cell lines in mouse xenografts

  • Interpreted metastasis-driving features in amplified generative cell image models


Paper: https://www.sciencedirect.com/science/article/pii/S2405471221001587.

Twitter summary: https://twitter.com/AssafZaritsky/status/1400044956262322177.

Press release and popular news: here (UTSW), here, here, here, here, and here.


And the paper was featured on the cover!