Our work on Artificial Intelligence and HCC immune signatures in now out in @JHepatology !#AI
#pathology @EASLnews @FondationARC @InfoCancerFoie @Stecarus @jnkath @GhaffariNarmin
@Eric_Vibert @INCa_veillePro
journal-of-hepatology.eu/article/S0168-…
👇👇👇
Immune and inflammatory gene signatures may predict HCC sensitivity to immunotherapy, and we thus train AI models to recognize tumors with activation of these signatures directly from HCC histology. We used approx. 350 HCC slides together with RNA seq data (TCGA series)
👇
We investigated different deep learning models, the first being a patch based approach
the other models were multiple instance learning based, where the analysis focus on some areas of the slides
We obtained good performances, in particular with the CLAM model, on the discovery set of 350 cases
we then validated our best models in a validation dataset of 139 cases with slides encoded in a different format, with different stainings and with a different RNA expression technology
Share this Scrolly Tale with your friends.
A Scrolly Tale is a new way to read Twitter threads with a more visually immersive experience.
Discover more beautiful Scrolly Tales like this.