Our interpretable machine learning in melanoma was published!

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!