Poster
Deep-Learning–Based Prediction of c-MET Status From Digitized H&E-Stained Non-small Cell Lung Cancer Tissue Samples
WCLC 2022
Study Background
Objective:
To develop a machine learning (ML)-powered method that identifies c-MET overexpression status directly from hematoxylin and eosin (H&E)-stained non-small cell lung cancer (NSCLC) samples.
To develop a machine learning (ML)-powered method that identifies c-MET overexpression status directly from hematoxylin and eosin (H&E)-stained non-small cell lung cancer (NSCLC) samples.
Authors
Rajan et al.