Zero-Shot and Few-Shot Learning for Lung Cancer Multi-Label Classification using Vision Transformer. (arXiv:2205.15290v2 [cs.CV] UPDATED)

Lung cancer is the leading cause of cancer-related death worldwide. Lung
adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC) are the most
common histologic subtypes of non-small-cell lung cancer (NSCLC). Histology is
an essential tool for lung cancer diagnosis. Pathologists make classifications
according to the dominant subtypes. Although morphology remains the standard
for diagnosis, significant tool needs to be developed to elucidate the
diagnosis. In our study, we utilize the pre-trained Vision Transformer (ViT)
model to classify multiple label lung …

arxiv cancer classification cv few-shot learning learning lung cancer transformer vision